Energy management for battery-powered reconfigurable computing platforms

We define portable reconfigurable computing platforms as those which have some form of configurable logic coupled with other on-chip or off-chip processing units such as soft processors, embedded processors, and voltage-scalable processors. In the first part of this paper, we present and test a unique methodology where we dynamically change the active area of a field programmable gate array (FPGA) to vary the battery usage and lifetime of the system, by running it on several different taskgraph structures and report an average of 14% and as high as 21%, less battery capacity used, as compared to nonoptimal execution. In the second part of this paper, we integrate the above methodology with more traditional voltage and frequency scaling techniques for portable systems and present a heuristic iterative algorithm for single and multiple processing units. The iterative heuristic algorithm finds a sequence of tasks along with an appropriate design point (implementation option) for each task, such that a deadline is met and the amount of battery energy used is as small as possible. We have used several real-world benchmarks to test the effectiveness of this methodology and we will present the results.     

Simultaneous nonrigid registration of multiple point sets and atlas construction

Group-wise registration of a set of shapes represented by unlabeled point-sets is a challenging problem since, usually this involves solving for point correspondence in a nonrigid motion setting. In this paper, we propose a novel and robust algorithm that is capable of simultaneously computing the mean shape represented by a probability density function from multiple unlabeled point-sets and registering them non-rigidly to this emerging mean shape. This algorithm avoids the correspondence problem by minimizing the Jensen-Shannon (JS) divergence between the point sets. We motivate the use of the JS divergence by pointing out its close relationship to hypothesis testing. We derive the analytic gradient of the cost function in order to efficiently achieve the optimal solution. JS-divergence is symmetric with no bias toward any of the given shapes to be registered and whose mean is being sought. A by product of the registration process is a probabilistic atlas defined as the convex combination of the probability densities of the input point sets being aligned. Our algorithm can be especially useful for creating atlases of various shapes present in images as well as for simultaneously (rigidly or non-rigidly) registering 3D range data sets without having to establish any correspondence. We present experimental results on real and synthetic data.     

Theorem Proving Guided Development of Formal Assertions in a Resource-Constrained Scheduler for High-Level Synthesis

This paper presents a formal specification and a proof of correctness for the widely-used Force-Directed List Scheduling (FDLS) algorithm for resource-constrained scheduling of data flow graphs in high-level synthesis systems. The proof effort is conducted using a higher-order logic theorem prover. During the proof effort many interesting properties of the FDLS algorithm are discovered. These properties are formally stated and proved in a higher-order logic theorem proving environment. These properties constitute a detailed set of formal assertions and invariants that should hold at various steps in the FDLS algorithm. They are then inserted as programming assertions in the implementation of the FDLS algorithm in a production-strength high-level synthesis system. When turned on, the programming assertions (1) certify whether a specific run of the FDLS algorithm produced correct schedules and, (2) in the event of failure, help discover and isolate programming errors in the FDLS implementation.We present a detailed example and several experiments to demonstrate the effectiveness of these assertions in discovering and isolating errors. Based on this experience, we discuss the role of the formal theorem proving exercise in developing a useful set of assertions for embedding in the scheduler code and argue that in the absence of such a formal proof checking effort, discovering such a useful set of assertions would have been an arduous if not impossible task.     

Fast Collision Detection Algorithms with Applications to Particle Flow

In this paper, we present efficient algorithms for collision detection of arbitrarily shaped rigid moving objects in a variety of interactive as well as non-interactive environments. The algorithms primarily consist of two stages. The first stage involves finding candidate objects for possible collisions. The second stage involves detecting exact (within a prespecified tolerance) collision between these candidates. The primary data structure used in the algorithms is an octree. In the first stage, we build an octree for the enclosure containing the objects, which is used to detect possible collisions. Assuming spatial/temporal coherence i.e., that the particles move slowly or that the time sampling is fast enough, the average time complexity of this stage can be shown to be O(n) (excluding the time complexity for a one time octree construction), where n is the number of particles. In the second stage, we build a surface-octree for each object. If the objects are convex and assuming coherence, the expected time complexity to detect precise (within a prespecified tolerance) collision for each pair is a constant (excluding the time complexity for a one time surface-octree construction). Therefore, the overall expected time complexity for convex object collision detection is linear with respect to n. For the concave objects, complexity analysis is nontrivial to perform and instead we provide a very practical (almost linear time) algorithm. We apply our algorithms to particle flow simulations by simulating flow density conditions often arising in granular flows.     

Experimental and theoretical study of semiconductor laser dynamics due to filtered optical feedback

We report experimental results on the nonlinear dynamical response of a semiconductor laser subjected to time-delayed (>5 ns), frequency selective, optical feedback from a Fabry-Pe/spl acute/rot interferometer type of filter. Three regimes of interest, based on the relative value of the filter bandwidth with respect to the relevant laser parameters (relaxation oscillation frequency and external cavity mode spacing), are identified, viz. a wide filter case, an intermediate filter width case, and a narrow filter case. The dynamical response of the laser is shown to be quite different in each of these regimes. The principal results are 1) the laser's linewidth enhancement factor, coupled with the nonlinear response of the filter, can be exploited to induce nonlinear dynamics in the instantaneous optical frequency of the laser light on a time scale related to the time-delay of the feedback, 2) a mode mismatch effect which arises from a detuning between the filter center frequency and the nearest external cavity mode and manifests itself in a reduction of the maximum light available for feedback, and 3) a reduction in, or even disappearance of, relaxation oscillations in the laser dynamics when a filter of appropriate width is chosen. More generally, it is observed that certain dynamics that occur due to unfiltered optical feedback may be suppressed when the feedback light is spectrally filtered.     

Modulatory Effects of Biosynthesized Gold Nanoparticles Conjugated with Curcumin and Paclitaxel on Tumorigenesis and Metastatic Pathways—In Vitro and In Vivo Studies

Background: Breast cancer is the most common cancer in women globally, and diagnosing it early and finding potential drug candidates against multi-drug resistant metastatic breast cancers provide the possibilities of better treatment and extending life. Methods: The current study aimed to evaluate the synergistic anti-metastatic activity of Curcumin (Cur) and Paclitaxel (Pacli) individually, the combination of Curcumin–Paclitaxel (CP), and also in conjugation with gold nanoparticles (AuNP–Curcumin (Au-C), AuNP–Paclitaxel (Au-P), and AuNP–Curcumin–Paclitaxel (Au-CP)) in various in vitro and in vivo models. Results: The results from combination treatments of CP and Au-CP demonstrated excellent synergistic cytotoxic effects in triple-negative breast cancer cell lines (MDA MB 231 and 4T1) in in vitro and in vivo mouse models. Detailed mechanistic studies were performed that reveal that the anti-cancer effects were associated with the downregulation of the expression of VEGF, CYCLIN-D1, and STAT-3 genes and upregulation of the apoptotic Caspase-9 gene. The group of mice that received CP combination therapy (with and without gold nanoparticles) showed a significant reduction in the size of tumor when compared to the Pacli alone treatment and control groups. Conclusions: Together, the results suggest that the delivery of gold conjugated Au-CP formulations may help in modulating the outcomes of chemotherapy. The present study is well supported with observations from cell-based assays, molecular and histopathological analyses.     

An accurate and efficient bayesian method for automatic segmentation of brain MRI

Automatic three-dimensional (3-D) segmentation of the brain from magnetic resonance (MR) scans is a challenging problem that has received an enormous amount of attention lately. Of the techniques reported in the literature, very few are fully automatic. In this paper, we present an efficient and accurate, fully automatic 3-D segmentation procedure for brain MR scans. It has several salient features; namely, the following. 1) Instead of a single multiplicative bias field that affects all tissue intensities, separate parametric smooth models are used for the intensity of each class. 2) A brain atlas is used in conjunction with a robust registration procedure to find a nonrigid transformation that maps the standard brain to the specimen to be segmented. This transformation is then used to: segment the brain from nonbrain tissue; compute prior probabilities for each class at each voxel location and find an appropriate automatic initialization. 3) Finally, a novel algorithm is presented which is a variant of the expectation-maximization procedure, that incorporates a fast and accurate way to find optimal segmentations, given the intensity models along with the spatial coherence assumption. Experimental results with both synthetic and real data are included, as well as comparisons of the performance of our algorithm with that of other published methods.     

ANALYSIS OF THE MULTIPLICITY PATTERNS OF A CSTR

Continuous changes in the residence time of a cooled continuously stirred tank reactor, in which a single, exothermic, first-order reaction occurs, may lead to one of six different multiplicity patterns. A simple technique is developed for the exact prediction of the multiplicity pattern existing for any set of parameter values and of the influence of changes in the parameter values on the transition from one pattern to another.     

Drug release rate method for a liposome preparation

An in vitro method was developed to determine the rate of drug release from a liposome formulation. Liposome formulation containing metaproterenol sulfate was evaluated for release of the drug over a 24-hour period in an end-over-end tumbler device. Drug release appeared to be a function of all the operating parameters, such as rotational speed of the end-over-end tumbler, temperature of suspension, and the geometry of sample container that is placed in the end-over-end tumbler device.