Singular value decomposition based computationally efficient algorithm for rapid dynamic near-infrared diffuse optical tomography

Purpose: A computationally efficient algorithm (linear iterative type) based on singular value decomposition (SVD) of the Jacobian has been developed that can be used in rapid dynamic near-infrared (NIR) diffuse optical tomography. Methods: Numerical and experimental studies have been conducted to prove the computational efficacy of this SVD-based algorithm over conventional optical image reconstruction algorithms. Results: These studies indicate that the performance of linear iterative algorithms in terms of contrast recovery (quantitation of optical images) is better compared to nonlinear iterative (conventional) algorithms, provided the initial guess is close to the actual solution. The nonlinear algorithms can provide better quality images compared to the linear iterative type algorithms. Moreover, the analytical and numerical equivalence of the SVD-based algorithm to linear iterative algorithms was also established as a part of this work. It is also demonstrated that the SVD-based image reconstruction typically requires O(NN2) operations per iteration, as contrasted with linear and nonlinear iterative methods that, respectively, requir O(NN3) and O(NN6) operations, with ``NN'' being the number of unknown parameters in the optical image reconstruction procedure. Conclusions: This SVD-based computationally efficient algorithm can make the integration of image reconstruction procedure with the data acquisition feasible, in turn making the rapid dynamic NIR tomography viable in the clinic to continuously monitor hemodynamic changes in the tissue pathophysiology.

An efficient algorithm for scheduling in bluetooth piconets and scatternets

Bluetooth is a short-range radio technology operating in the unlicensed industrial-scientific-medical (ISM) band at 2.45 GHz. A piconet is basically a collection of slaves controlled by a master. A scatternet, on the other hand, is established by linking several piconets together in an ad hoc fashion to yield a global wireless ad hoc network. This paper proposes a scheduling policy that aims to achieve increased system throughput and reduced packet delays while providing reasonably good fairness among all traffic flows in bluetooth piconets and scatternets. We propose a novel algorithm for scheduling slots to slaves for both piconets and scatternets using multi-layered parameterized policies. Our scheduling scheme works with real data and obtains an optimal feedback policy within prescribed parameterized classes of these by using an efficient two-timescale simultaneous perturbation stochastic approximation (SPSA) algorithm. We show the convergence of our algorithm to an optimal multi-layered policy. We also propose novel polling schemes for intra- and inter-piconet scheduling that are seen to perform well. We present an extensive set of simulation results and performance comparisons with existing scheduling algorithms. Our results indicate that our proposed scheduling algorithm performs better overall on a wide range of experiments over the existing algorithms for both piconets (Das et al. in INFOCOM, pp. 591–600, 2001; Lapeyrie and Turletti in INFOCOM conference proceedings, San Francisco, US, 2003; Shreedhar and Varghese in SIGCOMM, pp. 231–242, 1995) and scatternets (Har-Shai et al. in OPNETWORK, 2002; Saha and Matsumot in AICT/ICIW, 2006; Tan and Guttag in The 27th annual IEEE conference on local computer networks(LCN). Tampa, 2002). Our studies also confirm that our proposed scheme achieves a high throughput and low packet delays with reasonable fairness among all the connections.

An efficient algorithm for linear programming

A simple but efficient algorithm is presented for linear programming. The algorithm computes the projection matrix exactly once throughout the computation unlike that of Karmarkar’s algorithm where in the projection matrix is computed at each and every iteration. The algorithm is best suitable to be implemented on a parallel architecture. Complexity of the algorithm is being studied.

STEM+: A Fair and Efficient Algorithm for Scheduling on the DSCH in UMTS Networks

In Universal Mobile Telecommunication Systems (UMTS), the Downlink Shared Channel (DSCH) can be used for providing streaming services. The traffic model for streaming services is different from the commonly used continuously- backlogged model. Each connection specifies a required service rate over an interval of time, k, called the "control horizon". In this paper, our objective is to determine how k DSCH frames should be shared among a set of I connections. We need a scheduler that is efficient and fair and introduce the notion of discrepancy to balance the conflicting requirements of aggregate throughput and fairness. Our motive is to schedule the mobiles in such a way that the schedule minimizes the discrepancy over the k frames. We propose an optimal and computationally efficient algorithm, called STEM+. The proof of the optimality of STEM+, when applied to the UMTS rate sets is the major contribution of this paper. We also show that STEM+ performs better in terms of both fairness and aggregate throughput compared to other scheduling algorithms. Thus, STEM+ achieves both fairness and efficiency and is therefore an appealing algorithm for scheduling streaming connections.

An efficient reduction algorithm for computation of interconnect delay variability for statistical timing analysis in clock tree planning

In this paper, we propose a novel and efficient algorithm for modelling sub-65 nm clock interconnect-networks in the presence of process variation. We develop a method for delay analysis of interconnects considering the impact of Gaussian metal process variations. The resistance and capacitance of a distributed RC line are expressed as correlated Gaussian random variables which are then used to compute the standard deviation of delay Probability Distribution Function (PDF) at all nodes in the interconnect network. Main objective is to find delay PDF at a cheaper cost. Convergence of this approach is in probability distribution but not in mean of delay. We validate our approach against SPICE based Monte Carlo simulations while the current method entails significantly lower computational cost.

An optimal parallel algorithm for sparse matrix bandwidth reduction on a linear array

A simple and efficient algorithm for the bandwidth reduction of sparse symmetric matrices is proposed. It involves column-row permutations and is well-suited to map onto the linear array topology of the SIMD architectures. The efficiency of the algorithm is compared with the other existing algorithms. The interconnectivity and the memory requirement of the linear array are discussed and the complexity of its layout area is derived. The parallel version of the algorithm mapped onto the linear array is then introduced and is explained with the help of an example. The optimality of the parallel algorithm is proved by deriving the time complexities of the algorithm on a single processor and the linear array.

Parallel processor scheduling for minimizing total weighted tardiness using ant colony optimization

In the modern business environment, meeting due dates and avoiding delay penalties are very important goals that can be accomplished by minimizing total weighted tardiness. We consider a scheduling problem in a system of parallel processors with the objective of minimizing total weighted tardiness. Our aim in the present work is to develop an efficient algorithm for solving the parallel processor problem as compared to the available heuristics in the literature and we propose the ant colony optimization approach for this problem. An extensive experimentation is conducted to evaluate the performance of the ACO approach on different problem sizes with the varied tardiness factors. Our experimentation shows that the proposed ant colony optimization algorithm is giving promising results compared to the best of the available heuristics.

Recognition And Top-Down Generation Of Beta-Acyclic Database Schemes

Database schemes can be viewed as hypergraphs with individual relation schemes corresponding to the edges of a hypergraph. Under this setting, a new class of "acyclic" database schemes was recently introduced and was shown to have a claim to a number of desirable properties. However, unlike the case of ordinary undirected graphs, there are several unequivalent notions of acyclicity of hypergraphs. Of special interest among these are agr-, beta-, and gamma-, degrees of acyclicity, each characterizing an equivalence class of desirable properties for database schemes, represented as hypergraphs. In this paper, two complementary approaches to designing beta-acyclic database schemes have been presented. For the first part, a new notion called "independent cycle" is introduced. Based on this, a criterion for beta-acyclicity is developed and is shown equivalent to the existing definitions of beta-acyclicity. From this and the concept of the dual of a hypergraph, an efficient algorithm for testing beta-acyclicity is developed. As for the second part, a procedure is evolved for top-down generation of beta-acyclic schemes and its correctness is established. Finally, extensions and applications of ideas are described.

Mesh Processing for Computerized Facial Anthropometry

Understanding of the shape and size of different features of the human body from scanned data is necessary for automated design and evaluation of product ergonomics. In this paper, a computational framework is presented for automatic detection and recognition of important facial feature regions, from scanned head and shoulder polyhedral models. A noise tolerant methodology is proposed using discrete curvature computations, band-pass filtering, and morphological operations for isolation of the primary feature regions of the face, namely, the eyes, nose, and mouth. Spatial disposition of the critical points of these isolated feature regions is analyzed for the recognition of these critical points as the standard landmarks associated with the primary facial features. A number of clinically identified landmarks lie on the facial midline. An efficient algorithm for detection and processing of the midline, using a point sampling technique, is also presented. The results obtained using data of more than 20 subjects are verified through visualization and physical measurements. A color based and triangle skewness based schemes for isolation of geometrically nonprominent features and ear region are also presented. [DOI: 10.1115/1.3330420]

Visibility volumes for interactive path optimization

We describe a real-time system that supports design of optimal flight paths over terrains. These paths either maximize view coverage or minimize vehicle exposure to ground. A volume-rendered display of multi-viewpoint visibility and a haptic interface assists the user in selecting, assessing, and refining the computed flight path. We design a three-dimensional scalar field representing the visibility of a point above the terrain, describe an efficient algorithm to compute the visibility field, and develop visual and haptic schemes to interact with the visibility field. Given the origin and destination, the desired flight path is computed using an efficient simulation of an articulated rope under the influence of the visibility gradient. The simulation framework also accepts user input, via the haptic interface, thereby allowing manual refinement of the flight path.

On numerical implementation of an isotropic elastic-viscoplastic constitutive model for bulk metallic glasses

An efficient algorithm within the finite deformation framework is developed for finite element implementation of a recently proposed isotropic, Mohr-Coulomb type material model, which captures the elastic-viscoplastic, pressure sensitive and plastically dilatant response of bulk metallic glasses. The constitutive equations are first reformulated and implemented using an implicit numerical integration procedure based on the backward Euler method. The resulting system of nonlinear algebraic equations is solved by the Newton-Raphson procedure. This is achieved by developing the principal space return mapping technique for the present model which involves simultaneous shearing and dilatation on multiple potential slip systems. The complete stress update algorithm is presented and the expressions for viscoplastic consistent tangent moduli are derived. The stress update scheme and the viscoplastic consistent tangent are implemented in the commercial finite element code ABAQUS/Standard. The accuracy and performance of the numerical implementation are verified by considering several benchmark examples, which includes a simulation of multiple shear bands in a 3D prismatic bar under uniaxial compression.

Strip based coding for large images using wavelets

Thanks to advances in sensor technology, today we have many applications (space-borne imaging, medical imaging, etc.) where images of large sizes are generated. Straightforward application of wavelet techniques for above images involves certain difficulties. Embedded coders such as EZW and SPIHT require that the wavelet transform of the full image be buffered for coding. Since the transform coefficients also require storing in high precision, buffering requirements for large images become prohibitively high. In this paper, we first devise a technique for embedded coding of large images using zero trees with reduced memory requirements. A 'strip buffer' capable of holding few lines of wavelet coefficients from all the subbands belonging to the same spatial location is employed. A pipeline architecure for a line implementation of above technique is then proposed. Further, an efficient algorithm to extract an encoded bitstream corresponding to a region of interest in the image has also been developed. Finally, the paper describes a strip based non-embedded coding which uses a single pass algorithm. This is to handle high-input data rates. (C) 2002 Elsevier Science B.V. All rights reserved.

The restriction mapping problem revisited

In computational molecular biology, the aim of restriction mapping is to locate the restriction sites of a given enzyme on a DNA molecule. Double digest and partial digest are two well-studied techniques for restriction mapping. While double digest is NP-complete, there is no known polynomial-time algorithm for partial digest. Another disadvantage of the above techniques is that there can be multiple solutions for reconstruction. In this paper, we study a simple technique called labeled partial digest for restriction mapping. We give a fast polynomial time (O(n(2) log n) worst-case) algorithm for finding all the n sites of a DNA molecule using this technique. An important advantage of the algorithm is the unique reconstruction of the DNA molecule from the digest. The technique is also robust in handling errors in fragment lengths which arises in the laboratory. We give a robust O(n(4)) worst-case algorithm that can provably tolerate an absolute error of O(Delta/n) (where Delta is the minimum inter-site distance), while giving a unique reconstruction. We test our theoretical results by simulating the performance of the algorithm on a real DNA molecule. Motivated by the similarity to the labeled partial digest problem, we address a related problem of interest-the de novo peptide sequencing problem (ACM-SIAM Symposium on Discrete Algorithms (SODA), 2000, pp. 389-398), which arises in the reconstruction of the peptide sequence of a protein molecule. We give a simple and efficient algorithm for the problem without using dynamic programming. The algorithm runs in time O(k log k), where k is the number of ions and is an improvement over the algorithm in Chen et al. (C) 2002 Elsevier Science (USA). All rights reserved.

Stream-Close: Fast mining of Closed Frequent Itemsets in high speed data streams

With the emergence of large-volume and high-speed streaming data, the recent techniques for stream mining of CFIpsilas (closed frequent itemsets) will become inefficient. When concept drift occurs at a slow rate in high speed data streams, the rate of change of information across different sliding windows will be negligible. So, the user wonpsilat be devoid of change in information if we slide window by multiple transactions at a time. Therefore, we propose a novel approach for mining CFIpsilas cumulatively by making sliding width(ges1) over high speed data streams. However, it is nontrivial to mine CFIpsilas cumulatively over stream, because such growth may lead to the generation of exponential number of candidates for closure checking. In this study, we develop an efficient algorithm, stream-close, for mining CFIpsilas over stream by exploring some interesting properties. Our performance study reveals that stream-close achieves good scalability and has promising results.