On the efficiency of several VM provisioning strategies for workflows with multi-threaded tasks on clouds

Cloud computing promises the delivery of on-demand pay-per-use access to unlimited resources. Using these resources requires more than a simple access to them as most clients have certain constraints in terms of cost and time that need to be fulfilled. Therefore certain scheduling heuristics have been devised to optimize the placement of client tasks on allocated virtual machines. The applications can be roughly divided in two categories: independent bag-of-tasks and workflows. In this paper we focus on the latter and investigate a less studied problem, i.e., the effect the virtual machine allocation policy has on the scheduling outcome. For this we look at how workflow structure, execution time, virtual machine instance type affect the efficiency of the provisioning method when cost and makespan are considered. To aid our study we devised a mathematical model for cost and makespan in case single or multiple instance types are used. While the model allows us to determine the boundaries for two of our extreme methods, the complexity of workflow applications calls for a more experimental approach to determine the general relation. For this purpose we considered synthetically generated workflows that cover a wide range of possible cases. Results have shown the need for probabilistic selection methods in case small and heterogeneous execution times are used, while for large homogeneous ones the best algorithm is clearly noticed. Several other conclusions regarding the efficiency of powerful instance types as compared to weaker ones, and of dynamic methods against static ones are also made.     

Thermomechanical characteristics of calcium aluminate cement and sand tapes prepared by tape casting

The present paper concerns the mechanical characterization of calcium aluminate cement and sand tapes prepared by tape casting, including ultrasonic measurements of Young's modulus at high temperature and evaluation of four point flexural behavior after heat treatments in the range of 20–1400 °C. It is shown that dehydration strongly affects mechanical properties in the 400–900 °C range, but that treatments at temperatures higher than 1200 °C increase both Young's modulus and strength. By correlation with thermal and X-ray diffraction analyses, the evolutions of thermomechanical properties have been related to phase and microstructural changes when heating the material after hydration: conversion of hydrates and dehydration at low temperature, then, crystallization of C–A and C–A–S phases and finally sintering at the highest temperatures. In a last part, it is shown that the reinforcement by glass fibres enhances the mechanical properties, in particular in the temperature range of dehydration, and gives to the material a non-brittle behavior.     

Adding a rigid motion model to foreground detection: application to moving object detection in rivers

Object detection in a dynamic background is a challenging task in many computer vision applications. In some situations, the motion of objects can be predicted thanks to its regularity (e.g., vehicle motion, pedestrian motion). In this article, we propose to model such motion knowledge and to use it as additional information to help in foreground detection. The inclusion of object motion information provides a measure for distinguishing moving objects from a background that has similar sizes and brightness levels. This information is obtained by applying statistical methods on data obtained during the training period. When available, prior knowledge can be incorporated into the foreground detection process to improve robustness and to decrease false detection. We apply this framework to moving object detection in rivers, one of the situations in which classic background subtraction algorithms fail. Our experiments show that the incorporation of prior motion data into background subtraction improves object detection.     

The Active Space of Mexican Rice Borer Pheromone Traps

The Mexican rice borer, Eoreuma loftini (Dyar) (Lepidoptera: Crambidae), is an invasive pest of sugarcane, Saccharum spp., rice, Oryza sativa L., and other graminaceous crops in the United States. Traps baited with the synthetic female sex pheromone of E. loftini are used for monitoring and management of this invasive pest. However, the active space, or radius of attraction, of these traps is not known. Two field experiments examined the effect of intertrap distance on trap captures with hexagonal arrays of traps deployed in rice stubble habitat in Texas (2011) and Louisiana (2013). Trap capture increased with increasing intertrap distance. Trap interference occurred at intertrap distances ≤50 m in the 2011 experiment. Results from the experiment conducted in 2013 indicate that trap interference occurs at intertrap distances of 50 m, but not at distances ≥100 m. These results suggest that under field conditions, E. loftini pheromone traps attract males from distances of 50–100 m. The active space of pheromone traps also was examined under controlled wind conditions by direct observation of male response to detection of the female sex pheromone. Eoreuma loftini males responded to the pheromone blend by becoming active, fanning their wings, and rapidly walking in circles. The mean distance from the pheromone source at which males responded was 47.6 m. This work provides the first documentation of active space for traps baited with female sex pheromone for a crambid species, and these data will improve pheromone trap deployment strategies for E. loftini monitoring and management.     

Discovery and SAR of Novel 2,3‐Dihydroimidazo[1,2‐c]quinazoline PI3K Inhibitors: Identification of Copanlisib (BAY 80‐6946)

The phosphoinositide 3‐kinase (PI3K) pathway is aberrantly activated in many disease states, including tumor cells, either by growth factor receptor tyrosine kinases or by the genetic mutation and amplification of key pathway components. A variety of PI3K isoforms play differential roles in cancers. As such, the development of PI3K inhibitors from novel compound classes should lead to differential pharmacological and pharmacokinetic profiles and allow exploration in various indications, combinations, and dosing regimens. A screening effort aimed at the identification of PI3Kγ inhibitors for the treatment of inflammatory diseases led to the discovery of the novel 2,3‐dihydroimidazo[1,2‐c]quinazoline class of PI3K inhibitors. A subsequent lead optimization program targeting cancer therapy focused on inhibition of PI3Kα and PI3Kβ. Herein, initial structure–activity relationship findings for this class and the optimization that led to the identification of copanlisib (BAY 80‐6946) as a clinical candidate for the treatment of solid and hematological tumors are described.     

Achieving SCA Conformance Testing with Model-Based Testing

Time-to-market and implementation cost are high-priority considerations in the automation of digital hardware design. Nowadays, digital signal processing applications are implemented into fixed-point architectures due to its advantage of manipulating data with lower word-length. Thus, floating-point to fixed point conversion is mandatory. This conversion is translated into optimizing the integer word length and fractional word length. Optimizing the integer word-length can significantly reduce the cost when the application is tolerant to a low probability of overflow. In this paper, a new selective simulation technique to accelerate overflow effect analysis is introduced. A new integer word-length optimization algorithm that exploits this selective simulation technique is proposed to reduce both implementation cost and optimization time. The efficiency of our proposals is illustrated through experiments, where selective simulation technique allows accelerating the execution time of up to 1200 and 1000 when applied on Global Positioning System and on Fast Fourier Transform part (FFT) of Orthogonal Frequency Division Multiplexing chain respectively. Moreover, applying the optimization algorithm on the FFT part leads to a cost reduction between 17 to 22 % with respect to interval arithmetic and an acceleration factor of up to 617 with respect to classical max-1 algorithm.     

EgoSpaces: facilitating rapid development of context-aware mobile applications

Today's mobile applications require constant adaptation to their changing environments, or contexts. Technological advances have increased the pervasiveness of mobile computing devices such as laptops, handhelds, and embedded sensors. The sheer amount of context information available for adaptation places a heightened burden on application developers as they must manage and utilize vast amounts of data from diverse sources. Facilitating programming in this data-rich environment requires a middleware that provides context information to applications in an abstract form. In this paper, we demonstrate the feasibility of such a middleware that allows programmers to focus on high-level interactions among programs and to employ declarative abstract context specifications in settings that exhibit transient interactions with opportunistically encountered components. We also discuss the novel context-aware abstractions the middleware provides and the programming knowledge necessary to write applications using it. Finally, we provide examples demonstrating the infrastructure's ability to support differing tasks from a wide variety of application domains.