Seismic risk evaluation of steel structures based on low-cycle fatigue

This paper outlines a methodology to incorporate low-cycle fatigue in seismic risk evaluation of steel structures. The method is based on a simple cumulative damage model in which damage due to each plastic excursion is approximated by a Coffin-Manson type relationship. The parameters in this model are treated as random variables with distributions that are obtained from studies on the nonlinear seismic behavior of bilinear single-degree-of-freedom oscillators. The method is used to obtain an equivalent ‘single-excursion’ ductility demand which represents the same damage state as the low-cycle fatigue model. The proposed approach presents a realistic means of seismic risk evaluation and will provide a basis for establishing safer and more reliable steel structures.     

Failure-aware resource provisioning for hybrid Cloud infrastructure

Hybrid Cloud computing is receiving increasing attention in recent days. In order to realize the full potential of the hybrid Cloud platform, an architectural framework for efficiently coupling public and private Clouds is necessary. As resource failures due to the increasing functionality and complexity of hybrid Cloud computing are inevitable, a failure-aware resource provisioning algorithm that is capable of attending to the end-users quality of service (QoS) requirements is paramount. In this paper, we propose a scalable hybrid Cloud infrastructure as well as resource provisioning policies to assure QoS targets of the users. The proposed policies take into account the workload model and the failure correlations to redirect users’ requests to the appropriate Cloud providers. Using real failure traces and a workload model, we evaluate the proposed resource provisioning policies to demonstrate their performance, cost as well as performance–cost efficiency. Simulation results reveal that in a realistic working condition while adopting user estimates for the requests in the provisioning policies, we are able to improve the users’ QoS about 32% in terms of deadline violation rate and 57% in terms of slowdown with a limited cost on a public Cloud.     

A bound on the projective dimension of three cubics

We show that given any polynomial ring R over a field and any ideal JR which is generated by three cubic forms, the projective dimension of R/J is at most 36. We also settle the question of whether ideals generated by three cubic forms can have projective dimension greater than 4, by constructing one with projective dimension equal to 5.     

A proximity-aware load balancing in peer-to-peer-based volunteer computing systems

One of the main challenges in peer-to-peer-based volunteer computing systems is an efficient resource discovery algorithm. Load balancing is a part of resource discovery algorithm and aims to minimize the overall response time of the system. This paper introduces an analytical model based on distributed parallel queues to optimize the average response time of the system in a distributed manner. The proposed resource discovery algorithm consists of two phases. In the first phase, it selects peers in a load-balanced manner based on QoS constraints of request. In the second phase, a proximity-aware feature is applied to select the peer with minimum communication overhead among selected peers in the first phase. Two dispatching strategies are proposed for the load balancing based on stochastic analysis of routing in the distributed parallel queues. These policies adopt probabilistic and deterministic sequences to redirect requests to the capable peers in the system. Simulation results show that the proposed resource discovery algorithm improves the response time of user’s requests by a factor of 1.8 under a moderate load.     

Traxtor: An Automatic Software Test Suit Generation Method Inspired by Imperialist Competitive Optimization Algorithms

Journal of Electronic Testing - Software testing refers to a process which improves the quality of software systems and also is one of time and cost consuming stages in software development. Hence,...     

Accurate prediction of maximum hydrogen sulfide absorption capacity in sour gas prewash units of natural gas treating plants

A neuro-fuzzy model is proposed for accurate prediction of the maximum H₂S absorption capacity in aqueous phase over wide ranges of temperatures and salt concentrations. Predictions of the presented fuzzy model are much more accurate than those obtained through the available thermodynamic alternatives. The proposed neuro-fuzzy model can be used for accurate design of new prewash gas sweetening units at the upstream of amine sweetening plants in oil and gas industries.     

Motion estimation using learning automata

Block-matching algorithms (BMAs) are widely employed for motion estimation. BMAs divide input frames into several blocks and minimize an error function for each block to calculate motion vectors. Afterward, each motion vector is applicable for all of the pixels within the block. Since computing the error functions is resource intensive, many fast-search motion estimation algorithms have been suggested to reduce the computational cost. These fast algorithms provide a significant reduction in computation but often converge to a local minimum. A learning automaton is an adaptive decision-making unit that learns the optimal action through repeated interactions with its environment. Learning automata (LA) have been applied successfully to a wide range of applications including pattern recognition, dynamic channel assignment, and social network analysis. In this paper, we apply LA to motion estimation problem, which is one of the basic problems in computer vision. We compare the accuracy and performance of the suggested algorithms with other well-known BMAs. Interestingly, the obtained results indicate high efficiency and accuracy of the proposed methods. The results suggest that simplicity, efficiency, parallel nature, and accuracy of LA-based methods make them a good candidate to solve computer vision problems.     

The effect of nanoliposomal formulations on Staphylococcus epidermidis biofilm

Objective: The aim of the present study was to assess the in vitro antimicrobial activities of nanoliposomal formulations loaded with vancomycin or/and rifampin against the biofilm formed by Staphylococcus epidermidis at 37?°C under aerobic condition.

Materials and methods: Liposomal formulations were prepared by dehydration-rehydration (DRV) method and characterized for size, zeta potential and encapsulation efficacy. The ability of different formulations on eradication of bacterial biofilm was assessed through optical density ratio (OD_r) and the results implicate higher survival rates of S. epidermidis on biofilm. Positive control was defined as an OD_r?=?1.0.

Results: The zeta potential of anionic, cationic and PEGylated liposomes was ?35?±?2, 35?±?1 and 27?±?2?mV whereas the mean sizes of these liposomal formulations were 145?±?4, 134?±?1 and 142?±?6?nm, respectively. Encapsulation efficacy of rifampin and vancomycin was more than 60% and about 25%, respectively. Cationic liposomal rifampin lowered the OD_r to 0.61 and was the most effective formulations against S. epidermidis biofilm (p?Conclusion: The results of this study showed that rifampin-loaded liposomes were effective against bacterial biofilm.     

Solution‐processable exfoliated zeolite nanosheets purified by density gradient centrifugation

Highly crystalline exfoliated MFI‐nanosheets can pave the way for large‐scale deployment of sub‐500‐nm zeolite membranes due to their processing and packing advantages. Exfoliated MFI‐nanosheets prepared by melt compounding contain a large amount of polymer and unexfoliated particles which are detrimental to the fabrication of ultrathin zeolite membranes. Complete removal of polystyrene from the nanosheet suspension in toluene is demonstrated by centrifugation of the suspension across chlorobenzene as confirmed by thermogravimetric analysis (TGA) data and transmission electron microscopy (TEM) images. Rate‐zonal centrifugation in a nonlinear density gradient fractionated exfoliated MFI‐nanosheets from unexfoliated particles. The purified nanosheets were highly crystalline as indicated by high‐resolution TEM (HRTEM) and electron diffraction (ED). Coating of purified MFI‐nanosheets on a smooth α‐alumina support, fabricated by filtration of α‐alumina suspension, led to a compact, b‐oriented, 80‐nm‐thick film. A mild hydrothermal treatment of the film led to a 200‐nm‐thick membrane, which demonstrated molecular sieving properties. © 2013 American Institute of Chemical Engineers AIChE J, 59: 3458–3467, 2013