With the continuous downscaling of semiconductor processes, the growing power density and thermal issues in multicore processors become more and more challenging, thus reliable dynamic thermal management (DTM) is required to prevent severe challenges in system performance. The accuracy of the thermal profile, delivered to the DTM manager, plays a critical role in the efficiency and reliability of DTM, different sources of noise and variations in deep submicron (DSM) technologies severely affecting the thermal data that can lead to significant degradation of DTM performance. In this article, we propose a novel fault-tolerance scheme exploiting approximate computing to mitigate the DSM effects on DTM efficiency. Approximate computing in hardware design can lead to significant gains in energy efficiency, area, and performance. To exploit this opportunity, there is a need for design abstractions that can systematically incorporate approximation in hardware design which is the main contribution of our work. Our proposed scheme achieves 11.20% lower power consumption, 6.59% smaller area, and 12% reduction in the number of wires, while increasing DTM efficiency by 5.24%.
In this paper, we present new algorithm for the solution of the nonlinear high order multi-point boundary value problem with suitable multi boundary conditions. The algorithm is based on the semi-analytic technique and the solutions are calculated in the form of a rapid convergent series. It is observed that the method gives more realistic series solution that converges very rapidly in physical problems. Illustrative examples are provided to demonstrate the efficiency and simplicity of the proposed method in solving this type of multi- point boundary value problems.
In the lifetime process in some systems, most data cannot belong to one single population. In fact, it can represent several subpopulations. In such a case, the known distribution cannot be used to model data. Instead, a mixture of distribution is used to modulate the data and classify them into several subgroups. The mixture of Rayleigh distribution is best to be used with the lifetime process. This paper aims to infer model parameters by the expectation-maximization (EM) algorithm through the maximum likelihood function. The technique is applied to simulated data by following several scenarios. The accuracy of estimation has been examined by the average mean square error (AMSE) and the average classification success rate (ACSR). T
... Show MoreCadmium element is one of the group IIB and classified as heavy metal and effects on human health and environment. The present work concerns with the biosorption of Cd(II) ions from aqueous solution using the outer layer of onions. Adsorption of the used ions was found to be pH dependent and maximum removal of the ions by outer layer of onions and was found to be 99.7%.
The influence and hazard of fire flame are one of the most important parameters that affecting the durability and strength of structural members. This research studied the influence of fire flame on the behavior of reinforced concrete beams affected by repeated load. Nine self- compacted reinforced concrete beams were castellated, all have the same geometric layout (0.15x0.15x1.00) m, reinforcement details and compressive strength (50 Mpa). To estimate the effect of fire flame disaster, four temperatures were adopted (200, 300, 400 and 500) oC and two method of cooling were used (graduated and sudden). In the first cooling method, graduated, the tested beams were leaved to cool in air while in the second method, sudden, water splash was use
... Show MoreInferential methods of statistical distributions have reached a high level of interest in recent years. However, in real life, data can follow more than one distribution, and then mixture models must be fitted to such data. One of which is a finite mixture of Rayleigh distribution that is widely used in modelling lifetime data in many fields, such as medicine, agriculture and engineering. In this paper, we proposed a new Bayesian frameworks by assuming conjugate priors for the square of the component parameters. We used this prior distribution in the classical Bayesian, Metropolis-hasting (MH) and Gibbs sampler methods. The performance of these techniques were assessed by conducting data which was generated from two and three-component mixt
... Show MoreBackground: Dentin removed during root canal system instrumentation for creating adequate geometry for the canal and cleaning the canal. A new instrument had been marketed with the aim of optimum shaping of all parts of the canal system, however, no information present about the amount of dentin removal compared to conventional rotary system. This study investigated the amount of dentin removal when the canal instrumented by SAF compared with ProTaper by using high resolution computed tomography (micro CT). Materials and Methods: Twenty extracted single canalled teeth were utilized for this study; and randomly divided into 2 groups. In the first group, the root canals were prepared by using protaper rotary system till F2 and the root canal
... Show MoreThe removal of cadmium ions from simulated groundwater by zeolite permeable reactive barrier was investigated. Batch tests have been performed to characterize the equilibrium sorption properties of the zeolite in cadmium-containing aqueous solutions. Many operating parameters such as contact time, initial pH of solution, initial concentration, resin dosage and agitation speed were investigated. The best values of these parameters that will achieved removal efficiency of cadmium (=99.5%) were 60 min, 6.5, 50 mg/L, 0.25 g/100 ml and 270 rpm respectively. A 1D explicit finite difference model has been developed to describe pollutant transport within a groundwater taking the pollutant sorption on the permeable reactive barrier (PRB), which i
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