Stochastic optimization for adaptive labor staffing in service systems

Service systems are labor intensive. Further, the workload tends to vary greatly with time. Adapting the staffing levels to the workloads in such systems is nontrivial due to a large number of parameters and operational variations, but crucial for business objectives such as minimal labor inventory. One of the central challenges is to optimize the staffing while maintaining system steady-state and compliance to aggregate SLA constraints. We formulate this problem as a parametrized constrained Markov process and propose a novel stochastic optimization algorithm for solving it. Our algorithm is a multi-timescale stochastic approximation scheme that incorporates a SPSA based algorithm for ‘primal descent' and couples it with a ‘dual ascent' scheme for the Lagrange multipliers. We validate this optimization scheme on five real-life service systems and compare it with a state-of-the-art optimization tool-kit OptQuest. Being two orders of magnitude faster than OptQuest, our scheme is particularly suitable for adaptive labor staffing. Also, we observe that it guarantees convergence and finds better solutions than OptQuest in many cases.

Dataflow analysis for data-race free programs

Memory models for shared-memory concurrent programming languages typically guarantee sequential consistency (SC) semantics for datarace-free (DRF) programs, while providing very weak or no guarantees for non-DRF programs. In effect programmers are expected to write only DRF programs, which are then executed with SC semantics. With this in mind, we propose a novel scalable solution for dataflow analysis of concurrent programs, which is proved to be sound for DRF programs with SC semantics. We use the synchronization structure of the program to propagate dataflow information among threads without requiring to consider all interleavings explicitly. Given a dataflow analysis that is sound for sequential programs and meets certain criteria, our technique automatically converts it to an analysis for concurrent programs.

Loop transformations: convexity, pruning, and optimization

High-level loop transformations are a key instrument in mapping computational kernels to effectively exploit the resources in modern processor architectures. Nevertheless, selecting required compositions of loop transformations to achieve this remains a significantly challenging task; current compilers may be off by orders of magnitude in performance compared to hand-optimized programs. To address this fundamental challenge, we first present a convex characterization of all distinct, semantics-preserving, multidimensional affine transformations. We then bring together algebraic, algorithmic, and performance analysis results to design a tractable optimization algorithm over this highly expressive space. Our framework has been implemented and validated experimentally on a representative set of benchmarks running on state-of-the-art multi-core platforms.

Adaptive power optimization of on-chip SNUCA cache on tiled chip multicore architecture using remap policy

Advances in technology have increased the number of cores and size of caches present on chip multicore platforms(CMPs). As a result, leakage power consumption of on-chip caches has already become a major power consuming component of the memory subsystem. We propose to reduce leakage power consumption in static nonuniform cache architecture(SNUCA) on a tiled CMP by dynamically varying the number of cache slices used and switching off unused cache slices. A cache slice in a tile includes all cache banks present in that tile. Switched-off cache slices are remapped considering the communication costs to reduce cache usage with minimal impact on execution time. This saves leakage power consumption in switched-off L2 cache slices. On an average, there map policy achieves 41% and 49% higher EDP savings compared to static and dynamic NUCA (DNUCA) cache policies on a scalable tiled CMP, respectively.

Precoder optimization in cognitive radio with interference constraints

We consider precoding strategies at the secondary base station (SBS) in a cognitive radio network with interference constraints at the primary users (PUs). Precoding strategies at the SBS which satisfy interference constraints at the PUs in cognitive radio networks have not been adequately addressed in the literature so far. In this paper, we consider two scenarios: i) when the primary base station (PBS) data is not available at SBS, and ii) when the PBS data is made available at the SBS. We derive the optimum MMSE and Tomlinson-Harashima precoding (THP) matrix Alters at the SBS which satisfy the interference constraints at the PUs for the former case. For the latter case, we propose a precoding scheme at the SBS which performs pre-cancellation of the PBS data, followed by THP on the pre-cancelled data. The optimum precoding matrix filters are computed through an iterative search. To illustrate the robustness of the proposed approach against imperfect CSI at the SBS, we then derive robust precoding filters under imperfect CSI for the latter case. Simulation results show that the proposed optimum precoders achieve good bit error performance at the secondary users while meeting the interference constraints at the PUs.

Active-contour-based automated image quantitation techniques for Western Blot analysis

Western Blot analysis is an analytical technique used in Molecular Biology, Biochemistry, Immunogenetics and other Molecular Biology studies to separate proteins by electrophoresis. The procedure results in images containing nearly rectangular-shaped blots. In this paper, we address the problem of quantitation of the blots using automated image processing techniques. We formulate a special active contour (or snake) called Oblong, which locks on to rectangular shaped objects. Oblongs depend on five free parameters, which is also the minimum number of parameters required for a unique characterization. Unlike many snake formulations, Oblongs do not require explicit gradient computations and therefore the optimization is carried out fast. The performance of Oblongs is assessed on synthesized data and Western Blot Analysis images.

Lexicon-free, novel segmentation of online handwritten indic words

Research in the field of recognizing unlimited vocabulary, online handwritten Indic words is still in its infancy. Most of the focus so far has been in the area of isolated character recognition. In the context of lexicon-free recognition of words, one of the primary issues to be addressed is that of segmentation. As a preliminary attempt, this paper proposes a novel script-independent, lexicon-free method for segmenting online handwritten words to their constituent symbols. Feedback strategies, inspired from neuroscience studies, are proposed for improving the segmentation. The segmentation strategy has been tested on an exhaustive set of 10000 Tamil words collected from a large number of writers. The results show that better segmentation improves the overall recognition performance of the handwriting system.

Tensile behavior of a free-standing Pt-aluminide (PtAl) bond coat

The tensile behavior of a high activity stand-alone Pt-aluminide (PtAl) bond coat was evaluated by the micro-tensile test method at various temperatures (room temperature to 1100 degrees C) and strain rates (10(-5) s(-1)-10(-1) s(-1).) At all strain rates, the stress strain behavior of the stand-alone coating was significantly affected by the variation in temperature. The stress strain response was linear, indicating brittle behavior, at temperatures below the brittle ductile transition temperature (BDTT). The coating exhibited appreciable ductility (up to 2%) above the BDTT. The strength (both yield stress and ultimate tensile strength) of the coating decreased and its ductility increased with increasing temperature above the BDTT. The tensile behavior of the coating was sensitive to strain rate in the ductile regime, with its strength increasing with increasing strain rate at any given temperature. The BDTT of the coating was found to increase with increasing with increasing strain rate. The coating exhibited two distinct mechanisms of deformation above the BDTT. The transition temperature for the change of deformation mechanism also increased with increasing strain rate. (C) 2012 Acta Materialia Inc. Published by Elsevier Ltd. All rights reserved.

Effect of compressibility on the velocity gradient tensor at free shear flow boundaries

Analyses of the invariants of the velocity gradient ten- sor were performed on flow fields obtained by DNS of compressible plane mixing layers at convective Mach num- bers Mc=0:15 and 1.1. Joint pdfs of the 2nd and 3rd invariants were examined at turbulent/nonturbulent (T/NT) boundaries—defined as surfaces where the local vorticity first exceeds a threshold fraction of the maximum of the mean vorticity. By increasing the threshold from very small lev-els, the boundary points were moved closer into the turbulent region, and the effects on the pdfs of the invariants were ob-served. Generally, T/NT boundaries are in sheet-like regions at both Mach numbers. At the higher Mach number a distinct lobe appears in the joint pdf isolines which has not been ob-served/reported before. A connection to the delayed entrain-ment and reduced growth rate of the higher Mach number flow is proposed.

Multi-objective optimization of satellite image registration using discrete Pparticle swarm optimisation

A new multi-sensor image registration technique is proposed based on detecting the feature corner points using modified Harris Corner Detector (HDC). These feature points are matched using multi-objective optimization (distance condition and angle criterion) based on Discrete Particle Swarm Optimization (DPSO). This optimization process is more efficient as it considers both the distance and angle criteria to incorporate multi-objective switching in the fitness function. This optimization process helps in picking up three corresponding corner points detected in the sensed and base image and thereby using the affine transformation, the sensed image is aligned with the base image. Further, the results show that the new approach can provide a new dimension in solving multi-sensor image registration problems. From the obtained results, the performance of image registration is evaluated and is concluded that the proposed approach is efficient.

Simulation of length-preserving motions of flexible one dimensional oObjects using optimization

During the motion of one dimensional flexible objects such as ropes, chains, etc., the assumption of constant length is realistic. Moreover,their motion appears to be naturally minimizing some abstract distance measure, wherein the disturbance at one end gradually dies down along the curve defining the object. This paper presents purely kinematic strategies for deriving length-preserving transformations of flexible objects that minimize appropriate ‘motion’. The strategies involve sequential and overall optimization of the motion derived using variational calculus. Numerical simulations are performed for the motion of a planar curve and results show stable converging behavior for single-step infinitesimal and finite perturbations 1 as well as multi-step perturbations. Additionally, our generalized approach provides different intuitive motions for various problem-specific measures of motion, one of which is shown to converge to the conventional tractrix-based solution. Simulation results for arbitrary shapes and excitations are also included.

A practical approach for cross-functional vehicle body weight optimization

The goal of optimization in vehicle design is often blurred by the myriads of requirements belonging to attributes that may not be quite related. If solutions are sought by optimizing attribute performance-related objectives separately starting with a common baseline design configuration as in a traditional design environment, it becomes an arduous task to integrate the potentially conflicting solutions into one satisfactory design. It may be thus more desirable to carry out a combined multi-disciplinary design optimization (MDO) with vehicle weight as an objective function and cross-functional attribute performance targets as constraints. For the particular case of vehicle body structure design, the initial design is likely to be arrived at taking into account styling, packaging and market-driven requirements. The problem with performing a combined cross-functional optimization is the time associated with running such CAE algorithms that can provide a single optimal solution for heterogeneous areas such as NVH and crash safety. In the present paper, a practical MDO methodology is suggested that can be applied to weight optimization of automotive body structures by specifying constraints on frequency and crash performance. Because of the reduced number of cases to be analyzed for crash safety in comparison with other MDO approaches, the present methodology can generate a single size-optimized solution without having to take recourse to empirical techniques such as response surface-based prediction of crash performance and associated successive response surface updating for convergence. An example of weight optimization of spaceframe-based BIW of an aluminum-intensive vehicle is given to illustrate the steps involved in the current optimization process.

Thermal Rearrangement of Azido Ketones into Oxazoles via Azirines: One-Pot, Metal-Free Heteroannulation to Functionalized 1,3-Oxazoles

alpha-Azidoacetophenones were converted into 2-aryl-1,3-oxazole-4-carbaldehydes through rearrangement of the carbon framework upon exposure to DMF/POCl3. The unprecedented rearrangement occurs via alkenyl azides and 2H-azirines. A mechanism for this unusual reaction was proposed and evidenced.

Simulation of Deformation Texture Evolution During Multi Axial Forging of Interstitial Free Steel

Bulk texture measurement of multi-axial forged body center cubic interstitial free steel performed in this study using x-ray and neutron diffraction indicated the presence of a strong {101}aOE (c) 111 > single texture component. Viscoplastic self-consistent simulations could successfully predict the formation of this texture component by incorporating the complicated strain path followed during this process and assuming the activity of {101}aOE (c) 111 > slip system. In addition, a first-order estimate of mechanical properties in terms of highly anisotropic yield locus and Lankford parameter was also obtained from the simulations.

Clusters of bound particles in the derivative delta-function Bose gas

In this paper we discuss a novel procedure for constructing clusters of bound particles in the case of a quantum integrable derivative delta-function Bose gas in one dimension. It is shown that clusters of bound particles can be constructed for this Bose gas for some special values of the coupling constant, by taking the quasi-momenta associated with the corresponding Bethe state to be equidistant points on a single circle in the complex momentum plane. We also establish a connection between these special values of the coupling constant and some fractions belonging to the Farey sequences in number theory. This connection leads to a classification of the clusters of bound particles associated with the derivative delta-function Bose gas and allows us to study various properties of these clusters like their size and their stability under the variation of the coupling constant. (C) 2013 Elsevier B.V. All rights reserved.