Multiclass Core Vector Machine

Even though several techniques have been proposed in the literature for achieving multiclass classification using Support Vector Machine(SVM), the scalability aspect of these approaches to handle large data sets still needs much of exploration. Core Vector Machine(CVM) is a technique for scaling up a two class SVM to handle large data sets. In this paper we propose a Multiclass Core Vector Machine(MCVM). Here we formulate the multiclass SVM problem as a Quadratic Programming(QP) problem defining an SVM with vector valued output. This QP problem is then solved using the CVM technique to achieve scalability to handle large data sets. Experiments done with several large synthetic and real world data sets show that the proposed MCVM technique gives good generalization performance as that of SVM at a much lesser computational expense. Further, it is observed that MCVM scales well with the size of the data set.

Boxicity of Circular Arc Graphs

A k-dimensional box is a Cartesian product R(1)x...xR(k) where each R(i) is a closed interval on the real line. The boxicity of a graph G, denoted as box(G), is the minimum integer k such that G can be represented as the intersection graph of a collection of k-dimensional boxes. That is, two vertices are adjacent if and only if their corresponding boxes intersect. A circular arc graph is a graph that can be represented as the intersection graph of arcs on a circle. We show that if G is a circular arc graph which admits a circular arc representation in which no arc has length at least pi(alpha-1/alpha) for some alpha is an element of N(>= 2), then box(G) <= alpha (Here the arcs are considered with respect to a unit circle). From this result we show that if G has maximum degree Delta < [n(alpha-1)/2 alpha] for some alpha is an element of N(>= 2), then box(G) <= alpha. We also demonstrate a graph having box(G) > alpha but with Delta = n (alpha-1)/2 alpha + n/2 alpha(alpha+1) + (alpha+2). For a proper circular arc graph G, we show that if Delta < [n(alpha-1)/alpha] for some alpha is an element of N(>= 2), then box(G) <= alpha. Let r be the cardinality of the minimum overlap set, i.e. the minimum number of arcs passing through any point on the circle, with respect to some circular arc representation of G. We show that for any circular arc graph G, box(G) <= r + 1 and this bound is tight. We show that if G admits a circular arc representation in which no family of k <= 3 arcs covers the circle, then box(G) <= 3 and if G admits a circular arc representation in which no family of k <= 4 arcs covers the circle, then box(G) <= 2. We also show that both these bounds are tight.

River water quality response under hypothetical climate change scenarios in Tunga-Bhadra river, India

Analysis of climate change impacts on streamflow by perturbing the climate inputs has been a concern for many authors in the past few years, but there are few analyses for the impacts on water quality. To examine the impact of change in climate variables on the water quality parameters, the water quality input variables have to be perturbed. The primary input variables that can be considered for such an analysis are streamflow and water temperature, which are affected by changes in precipitation and air temperature, respectively. Using hypothetical scenarios to represent both greenhouse warming and streamflow changes, the sensitivity of the water quality parameters has been evaluated under conditions of altered river flow and river temperature in this article. Historical data analysis of hydroclimatic variables is carried out, which includes flow duration exceedance percentage (e.g. Q90), single low- flow indices (e.g. 7Q10, 30Q10) and relationships between climatic variables and surface variables. For the study region of Tunga-Bhadra river in India, low flows are found to be decreasing and water temperatures are found to be increasing. As a result, there is a reduction in dissolved oxygen (DO) levels found in recent years. Water quality responses of six hypothetical climate change scenarios were simulated by the water quality model, QUAL2K. A simple linear regression relation between air and water temperature is used to generate the scenarios for river water temperature. The results suggest that all the hypothetical climate change scenarios would cause impairment in water quality. It was found that there is a significant decrease in DO levels due to the impact of climate change on temperature and flows, even when the discharges were at safe permissible levels set by pollution control agencies (PCAs). The necessity to improve the standards of PCA and develop adaptation policies for the dischargers to account for climate change is examined through a fuzzy waste load allocation model developed earlier. Copyright (C) 2011 John Wiley & Sons, Ltd.

Minimization of Constraint Violation in Fuzzy Multiobjective Programming

Fuzzy multiobjective programming for a deterministic case involves maximizing the minimum goal satisfaction level among conflicting goals of different stakeholders using Max-min approach. Uncertainty due to randomness in a fuzzy multiobjective programming may be addressed by modifying the constraints using probabilistic inequality (e.g., Chebyshev’s inequality) or by addition of new constraints using statistical moments (e.g., skewness). Such modifications may result in the reduction of the optimal value of the system performance. In the present study, a methodology is developed to allow some violation in the newly added and modified constraints, and then minimizing the violation of those constraints with the objective of maximizing the minimum goal satisfaction level. Fuzzy goal programming is used to solve the multiobjective model. The proposed methodology is demonstrated with an application in the field of Waste Load Allocation (WLA) in a river system.

Fuzzy inference based data preprocessing for VBR video traffic prediction

Prediction of variable bit rate compressed video traffic is critical to dynamic allocation of resources in a network. In this paper, we propose a technique for preprocessing the dataset used for training a video traffic predictor. The technique involves identifying the noisy instances in the data using a fuzzy inference system. We focus on three prediction techniques, namely, linear regression, neural network and support vector regression and analyze their performance on H.264 video traces. Our experimental results reveal that data preprocessing greatly improves the performance of linear regression and neural network, but is not effective on support vector regression.

The radiation resistance of off-set series slots in microstrip line

The radiation resistance of off-set series slots has been calculated for microstrip lines using the method proposed by Breithaupt for strip lines. A suitable transformation is made to allow for the difference in structure. Curves relating the slot resistance to the microstrip length, width and off-set distance have been obtained. Microstrip slot antenna arrays are becoming important in applications where size and weight are of significance. The radiation resistance is a very significant parameter is the design of such arrays. Oliner first calculated the radiation conductance of centered series slots in strip transmission lines and that analysis was extended by Breithaupt to the off-set series slots in stripline. The radiation resistance of off-set series slots in microstrip lines is calculated in this paper and data are obtained for different slot lengths, slot widths and off-set values. An example of the use of these data in array antenna design in shown.

Fuzzy logic based TCSC supplementary controller for damping of inter area oscillations in power system

This paper describes an application of a FACTS supplementary controller for damping of inter area oscillations in power systems. A fuzzy logic controller is designed to regulate a thyristor controlled series capacitor (TCSC) in a multimachine environment to produce additional damping in the system. Simultaneous application of the excitation controller and proposed controller is also investigated. Simulation studies have been done with different types of disturbances and the results are shown to be consistent with the expected performance of the supplementary controller.

Possibility of chaos in interval friction experiments of martensites

Wuttig and Suzuki's model on anelastic nonlinearities in solids in the vicinity of martensite transformations is analysed numerically. This model shows chaos even in the absence of applied forcing field as a function of a temperature dependent parameter. Even though the model exhibits sustained oscillations as a function of the amplitude of the forcing term, it does not exactly capture the features of the experimental time series. We have improved the model by adding a symmetry breaking term. The improved model shows period doubling bifurcation as a function of the amplitude of the forcing term. The solutions of our improved model shows good resemblance with the nonsymmetric period four oscillation seen in the experiment. (C) 1999 Elsevier Science B.V. All rights reserved.

Extracting Three Dimensional Surface Model of Human Kidney from the Visible Human Data Set using Free Software

Three dimensional digital model of a representative human kidney is needed for a surgical simulator that is capable of simulating a laparoscopic surgery involving kidney. Buying a three dimensional computer model of a representative human kidney, or reconstructing a human kidney from an image sequence using commercial software, both involve (sometimes significant amount of) money. In this paper, author has shown that one can obtain a three dimensional surface model of human kidney by making use of images from the Visible Human Data Set and a few free software packages (ImageJ, ITK-SNAP, and MeshLab in particular). Images from the Visible Human Data Set, and the software packages used here, both do not cost anything. Hence, the practice of extracting the geometry of a representative human kidney for free, as illustrated in the present work, could be a free alternative to the use of expensive commercial software or to the purchase of a digital model.