A singular loop transformation framework based on non-singular matrices

In this paper, we discuss a loop transformation framework that is based on integer non-singular matrices. The transformations included in this framework are called Λ-transformations and include permutation, skewing and reversal, as well as a transformation calledloop scaling. This framework is more general than existing ones; however, it is also more difficult to generate code in our framework. This paper shows how integer lattice theory can be used to generate efficient code. An added advantage of our framework over existing ones is that there is a simple completion algorithm which, given a partial transformation matrix, produces a full transformation matrix that satisfies all dependences. This completion procedure has applications in parallelization and in the generation of code for NUMA machines. This work was supported by the Cornell Theory Center, NSF Presidential Young Investigator award #CCR-8958543. by NSF Grant #CCR-9008526, and by a grant from the Hewlett-Packard Company.     

Epileptic seizure classification in EEG signals using second-order difference plot of intrinsic mode functions

Epilepsy is a neurological disorder which is characterized by transient and unexpected electrical disturbance of the brain. The electroencephalogram (EEG) is a commonly used signal for detection of epileptic seizures. This paper presents a new method for classification of ictal and seizure-free EEG signals. The proposed method is based on the empirical mode decomposition (EMD) and the second-order difference plot (SODP). The EMD method decomposes an EEG signal into a set of symmetric and band-limited signals termed as intrinsic mode functions (IMFs). The SODP of IMFs provides elliptical structure. The 95% confidence ellipse area measured from the SODP of IMFs has been used as a feature in order to discriminate seizure-free EEG signals from the epileptic seizure EEG signals. The feature space obtained from the ellipse area parameters of two IMFs has been used for classification of ictal and seizure-free EEG signals using the artificial neural network (ANN) classifier. It has been shown that the feature space formed using ellipse area parameters of first and second IMFs has given good classification performance. Experimental results on EEG database available by the University of Bonn, Germany, are included to illustrate the effectiveness of the proposed method.     

Effect of alkali on filaments of poly(ethylene terephthalate) and its copolyesters

The alkali hydrolysis of poly(ethylene terephthalate), anionic copolymer of poly(ethylene terephthalate), and block copolymer of poly(ethylene terephthalate)–poly(ethylene glycol) is investigated under a variety of conditions of alkali concentration in aqueous bath, additives, time, and temperature. Measurements of loss in weight, linear density, breaking load, tenacity, elongation to break apart from intrinsic viscosity, fiber density, COOH-end group content, diameter of filaments, and scanning electron micrographs have been analyzed to identify the differences in the action of alkali on these polymer materials.     

The Network as a Storage Device: Dynamic Routing with Bounded Buffers

We study dynamic routing in store-and-forward packet networks where each network link has bounded buffer capacity for receiving incoming packets and is capable of transmitting a fixed number of packets per unit of time. At any moment in time, packets are injected at various network nodes with each packet specifying its destination node. The goal is to maximize the throughput, defined as the number of packets delivered to their destinations. In this paper, we make some progress on throughput maximization in various network topologies. Let n and m denote the number of nodes and links in the network, respectively. For line networks, we show that Nearest-to-Go (NTG), a natural distributed greedy algorithm, is -competitive, essentially matching a known lower bound on the performance of any greedy algorithm. We also show that if we allow the online routing algorithm to make centralized decisions, there is a randomized polylog(n)-competitive algorithm for line networks as well as for rooted tree networks, where each packet is destined for the root of the tree. For grid graphs, we show that NTG has a competitive ratio of while no greedy algorithm can achieve a ratio better than . Finally, for arbitrary network topologies, we show that NTG is -competitive, improving upon an earlier bound of O(mn). An extended abstract appeared in the Proceedings of the 8th Workshop on Approximation Algorithms for Combinatorial Optimization Problems, APPROX 2005, Berkeley, CA, USA, pp. 1–13, Lecture Notes in Computer Science, vol. 1741, Springer, Berlin. S. Angelov is supported in part by NSF Career Award CCR-0093117, NSF Award ITR 0205456 and NIGMS Award 1-P20-GM-6912-1. S. Khanna is supported in part by an NSF Career Award CCR-0093117, NSF Award CCF-0429836, and a US-Israel Binational Science Foundation Grant. K. Kunal is supported in part by an NSF Career Award CCR-0093117 and NSF Award CCF-0429836.     

Collusion set detection using graph clustering

Many mal-practices in stock market trading—e.g., circular trading and price manipulation—use the modus operandi of collusion. Informally, a set of traders is a candidate collusion set when they have “heavy trading” among themselves, as compared to their trading with others. We formalize the problem of detection of collusion sets, if any, in the given trading database. We show that naïve approaches are inefficient for real-life situations. We adapt and apply two well-known graph clustering algorithms for this problem. We also propose a new graph clustering algorithm, specifically tailored for detecting collusion sets. A novel feature of our approach is the use of Dempster–Schafer theory of evidence to combine the candidate collusion sets detected by individual algorithms. Treating individual experiments as evidence, this approach allows us to quantify the confidence (or belief) in the candidate collusion sets. We present detailed simulation experiments to demonstrate effectiveness of the proposed algorithms.     

Optical properties of CdS sintered film

Chemical method has been used to prepare cadmium sulphide by using cadmium, hydrochloric acid and H₂S. The reflection spectra of covered and uncovered sintered films of CdS have been recorded by ‘Hitachi spectrophotometer’ over the wavelength range 300–700 nm. The energy band gaps of these films have been calculated from reflection spectra. It is found that the energy band gap of both films is same as 2.41 eV. It is indicated that energy band gap of these films does not change. This value of band gap is in good agreement with the value reported by other workers. The measurement of photocurrent has also been carried out using Keithley High Resistance meter/ Electrometer. This film shows the high photosensitivity and high photocurrent decay. Thus so obtained films are suitable for fabrication of photo detectors and solar cells.     

Look Left, Look Right, Look Left Again: An Application of Fractal Symbolic Analysis to Linear Algebra Code Restructuring

Fractal symbolic analysis is a symbolic analysis technique for verifying the legality of program transformations. It is strictly more powerful than dependence analysis; for example, it can be used to verify the legality of blocking LU factorization with pivoting, a task for which dependence analysis is inadequate. In this paper, we show how fractal symbolic analysis can be used to convert between left- and right-looking versions of three kernels of central importance in computational science: triangular solve, Cholesky factorization, and LU factorization with pivoting.     

3D word spotting using leap motion sensor

Multimedia Tools and Applications - Leap motion sensor provides a new way of interaction with computers or mobile devices. With this sensor, users can write in air by moving palm or finger, thus,...     

Reactive extraction of itaconic acid using tri‐n‐butyl phosphate and aliquat 336 in sunflower oil as a non‐toxic diluent

Itaconic acid finds a place in various industrial applications. It can be produced by biocultivation in a clean and environment friendly route but recovery of the acid from the dilute stream of the bioreactor is an economic problem. Reactive extraction is a promising method to recover carboxylic acid but suffers from toxicity problems of the diluent and extractant employed. So there is need for a non‐toxic extractant and diluent or a combination of less toxic extractants in a non‐toxic diluent that can recover acid efficiently. Effect of different extractants: tri‐n‐butylphosphate (TBP) (an organophosporous compound) and Aliquat 336 (a quaternary amine) in sunflower oil was studied to find the best extractant–sunflower oil combination. Equilibrium complexation constant, K_E, values of 1.789 and 2.385 m³ kmol^?1, respectively, were obtained for itaconic acid extraction using TBP and Aliquat 336 in sunflower oil. The problem of toxicity in reactive extraction can be reduced by using a natural non‐toxic diluent (sunflower oil) with the extractant. Copyright © 2010 Society of Chemical Industry