YAARC: yet another approach to further reducing the rate of conflict misses

Traditional set associative caches are seriously prone to conflict misses. We propose an adapted new skewed associative architecture as an attempt to alleviate this problem. It has already been shown that skewed associative caches can reduce the rate of conflict misses by using different hash functions to index different banks. Building on this observation, we propose yet another approach to further reduce the rate of conflict misses, nicknamed YAARC (Yet Another Approach to Reducing Conflicts) that uses different hash functions to index into a single bank. Mathematical modeling and simulation results are exploited to evaluate the impact of YAARC on the rate of conflict misses. Mathematical analysis show the superiority of YAARC caches over set and skewed associative caches from the conflict miss point of view. Simulations, using some benchmarks from SPEC CPU2000 benchmark suit that former researchers have reported them as the best candidates for cache performance evaluation, also show nearly 43% conflict miss rate improvement for the skewed associative cache over the set associative cache, and nearly 31% improvement for the YAARC cache over the skewed associative cache. This implies that YAARC caches considerably outperform set and skewed associative caches from the conflict miss point of view. Since production of YAARC caches require a dispensable amount of hardware overhead, they can be considered as a cost effective approach to minimize the rate of conflict misses.

An energy-aware virtual machines consolidation method for cloud computing: Simulation and verification

Cloud systems have become an essential part of our daily lives owing to various Internet-based services. Consequently, their energy utilization has also become a necessary concern in cloud computing systems increasingly. Live migration, including several virtual machines (VMs) packed on in minimal physical machines (PMs) as virtual machines consolidation (VMC) technique, is an approach to optimize power consumption. In this article, we have proposed an energy-aware method for the VMC problem, which is called energy-aware virtual machines consolidation (EVMC), to optimize the energy consumption regarding the quality of service guarantee, which comprises: (1) the support vector machine classification method based on the utilization rate of all resource of PMs that is used for PM detection in terms of the amount' load; (2) the modified minimization of migration approach which is used for VM selection; (3) the modified particle swarm optimization which is implemented for VM placement. Also, the evaluation of the functional requirements of the method is presented by the formal method and the non-functional requirements by simulation. Finally, in contrast to the standard greedy algorithms such as modified best fit decreasing, the EVMC decreases the active PMs and migration of VMs, respectively, 30%, 50% on average. Also, it is more efficient for the energy 30% on average, resources and the balance degree 15% on average in the cloud.     

3D human pose estimation from image using couple sparse coding

Recent studies have demonstrated that high-level semantics in data can be captured using sparse representation. In this paper, we propose an approach to human body pose estimation in static images based on sparse representation. Given a visual input, the objective is to estimate 3D human body pose using feature space information and geometrical information of the pose space. On the assumption that each data point and its neighbors are likely to reside on a locally linear patch of the underlying manifold, our method learns the sparse representation of the new input using both feature and pose space information and then estimates the corresponding 3D pose by a linear combination of the bases of the pose dictionary. Two strategies for dictionary construction are presented: (i) constructing the dictionary by randomly selecting the frames of a sequence and (ii) selecting specific frames of a sequence as dictionary atoms. We analyzed the effect of each strategy on the accuracy of pose estimation. Extensive experiments on datasets of various human activities show that our proposed method outperforms state-of-the-art methods.     

On using a new strain of Acidithiobacillus ferridurans for bioleaching of low-grade uranium

ABSTRACT

In the present investigation, isolation and determination of a new strain of Acidithiobacillus ferridurans SBU-SH2 from an Iranian sulfur hot spring are carried out and then it is used to evaluate the performance of uranium bioleaching from a low-grade natural resource host. The efficiency of uranium recovery is studied by considering the influence of experimental factors like pulp density, pH value, temperature, and source of energy. Experimental tests reveal that more than 96% of uranium is recovered at 35°C, initial pH 2.5, agitation speed of 120 rpm, and pulp density of 5% in about 1 week.     

Machine cell/part family formation considering processing times and machine capacities: a simulated annealing approach

Binary machine-part matrices have been widely used to identify machine groups and part families. The methods based on binary machine-part matrices mostly focus on the reduction of setup times and material handling costs. However, some other objectives such as the maximization of within-cell utilization and minimization of workload imbalance may not be achieved without considering other important factors such as processing times, lot sizes and machine capacities. Ignoring the processing times may violate the capacity constraints, and thus lead to an infeasible solution. This paper proposes a generalized grouping efficiency considering processing times and lot sizes. A simulated annealing algorithm is developed to solve the grouping problem and a neural network approach is used to provide a seed solution. Our computational experience indicates that the proposed algorithm is able to find a near optimum solution with less number of duplicated machines and better workload balance as compared to the approach reported in the literature.     

A low-power 2.4-GHz transmitter/receiver CMOS IC

A 2.4-GHz CMOS receiver/transmitter incorporates circuit stacking and noninvasive baseband filtering to achieve a high sensitivity with low power dissipation. Using a single 1.6-GHz local oscillator, the transceiver employs two upconversion and downconversion stages while providing on-chip image rejection filtering. Realized in a 0.25-/spl mu/m digital CMOS technology, the receiver exhibits a noise figure of 6 dB and consumes 17.5 mW from a 2.5-V supply, and the transmitter delivers an output power of 0 dBm with a power consumption of 16 mW.     

A stochastic model on the profitability of loyalty programs

Effectiveness of customers’ loyalty programs has been the focal point of some recent studies. While empirical research shows mixed findings, analytical studies on the efficacy of loyalty programs are in their early stages. In this paper, we develop an analytical model on the profitability of loyalty programs in which customers’ valuations along with their satisfaction levels are incorporated as stochastic variables. The model consists of a revenue-maximizing firm selling a product through two periods. A loyalty reward is offered to two-period buyers in the form of an absolute-value discount on the price in the second period. The satisfaction level is represented by the difference between a customer’s original and post-purchase valuation. The formulation yields a stochastic programming problem with a nonlinear non-convex objective function. The problem is solved in terms of the model parameters. The results reveal that depending on the mean and variance of the satisfaction levels, the firm may be better off not to offer a loyalty reward. Specifically, if the mean of satisfaction levels turns out to be positive with a coefficient of variation less than a certain threshold, not adopting the loyalty program is optimal.     

Procedure effect on the physical and mechanical properties of the extruded wood plastic composites

This article investigates the effect of raw material preparation on the mechanical and physical properties in wood‐plastic composite (WPC) production. Four possible procedures in material preparation to obtain a determined level of wood content are: (i) to use and feed raw materials in the same ratio of the desired composition (single stage), (ii) to use the batch of granules of the same composition (two‐stage), (iii) to add wood to the batch of granules having a lower wood content, (iv) to add polymer to the batch of granules having a higher wood content. The main question then is that, while it is economically attractive to use granules of a fixed wood content in all productions, whether there are noticeable differences in final properties of the products. The examined compositions were 50, 60, and 70 wt% of wood content which are considered as highly filled WPCs and mainly used in the WPC markets. Thus, 12 sets of WPC profiles were manufactured and the processing conditions (temperature, pressure, and outlet velocity) recorded. The flexural properties, impact strength, density, and water uptake were measured. Results revealed that in the production of WPCs with 50 and 70 wt% of wood content, using the WPC granules with the same composition yields better physical and mechanical properties. However, for producing WPC with 60 wt% of wood content, using WPC granules with 70 wt% of wood and adding appropriate amount of polymer exhibit better results. POLYM. COMPOS. 34:1349–1356, 2013. © 2013 Society of Plastics Engineers