PASTA: a power-aware solution to scheduling of precedence-constrained tasks on heterogeneous computing resources

Power efficiency is one of the main challenges in large-scale distributed systems such as datacenters, Grids, and Clouds. One can study the scheduling of applications in such large-scale distributed systems by representing applications as a set of precedence-constrained tasks and modeling them by a Directed Acyclic Graph. In this paper we address the problem of scheduling a set of tasks with precedence constraints on a heterogeneous set of Computing Resources (CRs) with the dual objective of minimizing the overall makespan and reducing the aggregate power consumption of CRs. Most of the related works in this area use Dynamic Voltage and Frequency Scaling (DVFS) approach to achieve these objectives. However, DVFS requires special hardware support that may not be available on all processors in large-scale distributed systems. In contrast, we propose a novel two-phase solution called PASTA that does not require any special hardware support. In its first phase, it uses a novel algorithm to select a subset of available CRs for running an application that can balance between lower overall power consumption of CRs and shorter makespan of application task schedules. In its second phase, it uses a low-complexity power-aware algorithm that creates a schedule for running application tasks on the selected CRs. We show that the overall time complexity of PASTA is $O(p.v^{2})$ where $p$ is the number of CRs and $v$ is the number of tasks. By using simulative experiments on real-world task graphs, we show that the makespan of schedules produced by PASTA are approximately 20 % longer than the ones produced by the well-known HEFT algorithm. However, the schedules produced by PASTA consume nearly 60 % less energy than those produced by HEFT. Empirical experiments on a physical test-bed confirm the power efficiency of PASTA in comparison with HEFT too.     

Surface Patches from Unorganized Space Curves

Recent 3D sketch tools produce networks of three‐space curves that suggest the contours of shapes. The shapes may be non‐manifold, closed three‐dimensional, open two‐dimensional, or mixed. We describe a system that automatically generates intuitively appealing piecewise‐smooth surfaces from such a curve network, and an intelligent user interface for modifying the automatically chosen surface patches. Both the automatic and the semi‐automatic parts of the system use a linear algebra representation of the set of surface patches to track the topology. On complicated inputs from ILoveSketch [ [BBS08] ], our system allows the user to build the desired surface with just a few mouse‐clicks.     

Estimating the rate constant in second-order kinetics using hard-soft-net analyte signal (HS-NAS) method

Rank deficiency is the major problem associated with the chemometrics modeling of the second-order chemical reactions of the form of A + B → C. In this article, the application of the hard-soft-net analyte signal (HS-NAS), as a newly proposed method in our research group, is described for modeling of second-order reactions. This combined hard-soft method is based on the net analyte signal (NAS) concept, which is defined as a part of total signal that is directly related to the concentration of the component of interest. Therefore, concentration changes versus time can be obtained by calculating NAS for any chemical species involved in the reaction without requiring any pure component spectra or extra runs. The power of the method was verified by applying it to the resolution of simulated data sets containing noises added at different levels. The resolution of the second-order reaction between amoxicillin and 1, 2-naphthoqoinone was also tested as a real chemical system.     

Preparation of Al2O3–TiB2 nanocomposite powder by mechanochemical reaction between Al,B2O3 and Ti

Mechanochemical processing is a novel technique for the synthesis of nano-sized materials. This research is based on the production of Al₂O₃–TiB₂ nanocomposite powder using mechanochemical processing. For this purpose, a mixture of aluminum, titanium and boron oxide powders was subjected to high energy ball milling. The structural evaluation of powder particles after different milling times was conducted by X-ray diffractometry (XRD), scanning electron microscopy (SEM), and transmission electron microscopy (TEM). The results showed that during ball milling the Al/B₂O₃/Ti reacted with a combustion mode producing Al₂O₃–TiB₂ nanocomposite. In the final stage of milling, the crystallite sizes of Al₂O₃ and TiB₂ were estimated to be less than 50 nm.     

Equilibrium,kinetic and thermodynamic study of removal of reactive orange 12 on platinum nanoparticle loaded on activated carbon as novel adsorbent

The proposed research describes the synthesis and characterization of platinum nanoparticles loaded on activated carbon (Pt-NP-AC) and its efficient application as novel adsorbent for efficient removal of reactive orange 12 (RO-12). The influences of effective parameters following the optimization of variables on removal percentages, their value was set as 0.015 g Pt-NP-AC, pH 1, contact time of 13 min. At optimum values of all variables at 25 and 50 mgL⁻¹ of RO-12 enthalpy (ΔH⁰) and entropy (ΔS⁰) changes was found to be 59.89 and 225.076, respectively, which negative value of ΔG⁰ shows a spontaneous nature, and the positive values of ΔH⁰ and ΔS⁰ indicate the endothermic nature and adsorption organized of dye molecule on the adsorbent surface. Experimental data was fitted to different kinetic models including first-order, pseudo-second-order, Elovich and intra-particle diffusion models, and it was seen that the adsorption process follows pseudo-second-order model in consideration to intra-particle diffusion mechanism. At optimum values of all variables, the adsorption process follows the second-order kinetic and Langmuir isotherm model with adsorption capacity 285.143 mg g⁻¹ at room temperature.     

Fuel size effect on pinewood combustion in a packed bed

In this paper, particle size effect on pinewood combustion in a stationary packed bed was investigated. Mass loss rate, temperature profile at different bed locations and gas compositions in the out-of-bed flue gases were measured at a fixed primary air flow rate. Pinewood cubes was fired with size ranging from 5 to 35 mm. A unique numerical model applicable to thermally thick particles was proposed and relevant equations were solved to simulate the non-homogeneous characteristics of the burning process. It is found that at the operating conditions of the current study, smaller particles are quicker to ignite than larger particles and have distinctive combustion stages; burning rate is also higher with smaller fuel size; and smaller fuels have a thinner reaction zone and result in both higher CO and CH₄ concentrations in the out-of-bed flue gases; on the other hand, larger particles produced a higher flame temperature and result in higher H₂ concentration in the flue gases. Larger particles also cause the combustion process becoming more transient where the burning rate varies for most part of the combustion process.     

High yield gold nanoparticle‐based DNA isolation method for human papillomaviruses genotypes from cervical cancer tissue samples

Gold nanoparticles (AuNPs) are commonly used in biosensors of various kinds. However, its application to extract DNA from cancer tissues has not been extensively studied. The purification of DNA from cancer tissues is an important step in diagnostic and therapeutic development. Almost, all cervical cancer cases are associated with high‐risk human papillomavirus (HR‐HPV) infection. Accurate viral diagnosis has so far relied on the extraction of adequate amounts of DNA from formalin‐fixed, paraffin‐embedded (FFPE) tissue samples. Till now, no specific and sensitive DNA purification method has been introduced for the extraction of HR‐HPV from FFPE tissue. Since the commercially available purification kits are not sensitive and specific enough for HR‐HPV DNA targets, in this study, a DNA purification method was designed based on AuNPs to purify sufficient amounts of HR‐HPV DNA from cervical cancer tissue samples. AuNPs were coated with a series of oligonucleotide probes to hybridize to specific DNA sequences of HR‐HPV genotypes. Results showed that 733 out of 800 copies of type‐specific HPV DNA were recovered with complete specificity, compared to 36 copies with a standard commercial kit (Qiagen FFPE). The high yield of DNA (91.6%) is the main advantage of the AuNPs‐probe purification method.Inspec keywords: cancer, biological tissues, microorganisms, gold, DNA, lab‐on‐a‐chip, gynaecology, purification, biochemistry, molecular biophysics, nanoparticles, nanomedicine, cellular biophysicsOther keywords: specific extraction method, cervical cancer tissue samples, high‐risk human papillomavirus infection, paraffin‐embedded tissue samples, specific DNA purification method, sensitive DNA purification method, FFPE tissue, HR‐HPV DNA targets, specific DNA sequences, HR‐HPV genotypes, type‐specific HPV DNA, AuNP‐probe purification method, gold nanoparticle‐based DNA isolation method, oligonucleotide, human papillomaviruse genotypes, clinical samples, Au     

Rapid determination of soil unconfined compressive strength using reflectance spectroscopy

Bulletin of Engineering Geology and the Environment - Understanding the physical and especially mechanical properties of forest soils is very important in forest engineering operations including...