A Strength Pareto Evolutionary Algorithm for live migration of multiple interdependent virtual machines in data centers

Although live VM migration has been intensively studied, the problem of live migration of multiple interdependent VMs has hardly been investigated. The most important problem in the live migration of multiple interdependent VMs is how to schedule VM migrations as the schedule will directly affect the total migration time and the total downtime of those VMs. Aiming at minimizing both the total migration time and the total downtime simultaneously, this paper presents a Strength Pareto Evolutionary Algorithm 2 (SPEA2) for the multi-VM migration scheduling problem. The SPEA2 has been evaluated by experiments, and the experimental results show that the SPEA2 can generate a set of VM migration schedules with a shorter total migration time and a shorter total downtime than an existing genetic algorithm, namely Random Key Genetic Algorithm (RKGA). This paper also studies the scalability of the SPEA2.

Milling innovations at Rocky Point

This paper reviews the innovations that have been introduced in the milling train at Rocky Point mill since 2001 and provides some operational, performance and maintenance comparisons of the technologies in use. The decision to install BHEM mills in the #2 and #3 mill positions to complement the six-roll mills in the #1 and #4 mill positions has proven a good one. Satisfactory performance is being obtained by these mills while maintenance costs are significantly less. Very good #1 mill extraction and final bagasse moisture content are being achieved. The innovation of using Hägglunds hydraulic drives at higher speed…

Programming an FPGA to Emulate the Dynamics of DC Machines

This paper presents the programming an FPGA (Field Programmable Gate Array) to emulate the dynamics of DC machines. FPGA allows high speed real time simulation with high precision. The described design includes block diagram representation of DC machine, which contain all arithmetic and logical operations. The real time simulation of the machine in FPGA is controlled by user interfaces they are Keypad interface, LCD display on-line and digital to analog converter. This approach provides emulation of electrical machine by changing the parameters. Separately Exited DC machine implemented and experimental results are presented.

Real-time simulation of electrical machines on FPGA platform

This paper presents real-time simulation models of electrical machines on FPGA platform. Implementation of the real-time numerical integration methods with digital logic elements is discussed. Several numerical integrations are presented. A real-time simulation of DC machine is carried out on this FPGA platform and important transient results are presented. These results are compared to simulation results obtained through a commercial off-line simulation software.

The effect of ball milling on the melting behavior of Sn-Cu-Ag eutectic alloy

Sn-Ag-Cu (SAC) solder alloys are the best Pb free alternative for electronic industry. Since their introduction, efforts are made to improve their efficacies by tuning the processing and composition to achieve lower melting point and better wettability. Nanostructured alloys with large boundary content are known to depress the melting points of metals and alloys. In this article we explore this possibility by processing prealloyed SAC alloys close to SAC305 composition (Sn-3wt%Ag-0.5wt%Cu) by mechanical milling which results in the formation of nanostructured alloys. Pulverisette ball mill (P7) and Vibratory ball mills are used to carry out the milling of the powders at room temperature and at lower temperatures (-104 A degrees C), respectively. We report a relatively smaller depression of melting point ranging up to 5 A degrees C with respect to original alloys. The minimum grain sizes achieved and the depression of melting point are similar for both room temperature and low-temperature processed samples. An attempt has been made to rationalize the observations in terms of the basic processes occurring during the milling.

Comparison of decision tree, support vector machines, and Bayesian network approaches for classification of falls in Parkinson’s disease

Being able to accurately predict the risk of falling is crucial in patients with Parkinson’s dis- ease (PD). This is due to the unfavorable effect of falls, which can lower the quality of life as well as directly impact on survival. Three methods considered for predicting falls are decision trees (DT), Bayesian networks (BN), and support vector machines (SVM). Data on a 1-year prospective study conducted at IHBI, Australia, for 51 people with PD are used. Data processing are conducted using rpart and e1071 packages in R for DT and SVM, con- secutively; and Bayes Server 5.5 for the BN. The results show that BN and SVM produce consistently higher accuracy over the 12 months evaluation time points (average sensitivity and specificity > 92%) than DT (average sensitivity 88%, average specificity 72%). DT is prone to imbalanced data so needs to adjust for the misclassification cost. However, DT provides a straightforward, interpretable result and thus is appealing for helping to identify important items related to falls and to generate fallers’ profiles.

Field evaluation of spinosad as a grain protectant for stored wheat in Australia: efficacy against Rhyzopertha dominica (F.) and fate of residues in whole wheat and milling fractions

The potential of spinosad as a grain protectant for the lesser grain borer, Rhyzopertha dominica, was investigated in a silo-scale trial on wheat stored in Victoria, Australia. Rhyzopertha dominica is a serious pest of stored grain, and its resistance to protectants and the fumigant phosphine is becoming more common. This trial follows earlier laboratory research showing that spinosad may be a useful pest management option for this species. Wheat (300 t) from the 2005 harvest was treated with spinosad 0.96 mg/kg plus chlorpyrifos-methyl 10 mg/kg in March 2006, and samples were collected at intervals during 7.5 month storage to determine efficacy and residues in wheat and milling fractions. Chlorpyrifos-methyl is already registered in Australia for control of several other pest species, and its low potency against R. dominica was confirmed in laboratory-treated wheat. Grain moisture content was stable at about 10%, but grain temperature ranged from 29.3°C in March to 14.0°C in August. Bioassays of all treated wheat samples over 7.5 months resulted in 100% adult mortality after 2 weeks exposure and no live progeny were produced. In addition, no live grain insects were detected during outload sampling after a 9 month storage. Spinosad and chlorpyrifos-methyl residues tended to decline during storage, and residues were higher in the bran layer than in either wholemeal or white flour. This field trial confirmed that spinosad was effective as a grain protectant targeting R. dominica.

Size effect on the lattice parameter of KCl during mechanical milling

The size effect on the lattice parameter of ionic KCl nanocrystals was studied systematically during mechanical milling of Pure KCl powder under vacuum. The results suggest anomalous lattice expansion, with the lattice parameter increasing from 6.278 angstrom at d = 6 mu m to 6.30307 angstrom at d = 85 mn. The defects generated during ball milling of KCl and surface stress are deemed to be responsible for this lattice parameter expansion. (C) 2009 Acta Materialia Inc. Published by Elsevier Ltd. All rights reserved.

Commercial products from bio-active extractives in cypress milling residues.

Extractive components obtained from milling residues of white cypress were studied for chemical identity and bioactivity with a view to developing a commercial use for these components, thus increasing the value of the residues and improving the economics of cypress sawn wood production. Extracts obtained by solvent or steam extraction techniques from cypress sawdust were each fractionated by a range of techniques into groups of similar compounds. Crude extracts and fractions were screened against a range of agricultural pests and diseases, including two fungi, subterranean termites, fruit spotting bugs, two-spotted mites, thrips, heliothis, banana scab moths, silverleaf whiteflies, cattle tick adults and larvae, and ruminant gastrointestinal nematodes. Additional screening was undertaken where encouraging results were achieved, for two-spotted mites, thrips, silverleaf whiteflies, cattle tick adults and ruminant gastrointestinal nematodes. After considering degrees of efficacy against, and economic importance of, the agricultural pests, and likely production costs of extracts and fractions, the crude extract (oil) produced by steam distillation was chosen for further study against silverleaf whitefly. A useful degree of control was achievable when this oil was applied to tomato or eggplant at 0.1%, with much less harmful effects on a beneficial insect. Activity of the oil against silverleaf whitefly was undiminished 3.5 years after it was generated. There was little benefit from supplementing the extract with co-formulated paraffinic oil. From the steam distilled oil, fifty-five compounds were characterised, thirty-five compounds representing 92.478 % of the oil, with guaiol (20.8%) and citronellic acid (15.9%) most abundant. These two compounds, and a group of oxygenated compounds containing bulnesol and a range of eudesmols, were found to account for most of the activity against silverleaf whitefly. This application was recommended for first progression to commercialisation.

Distance Relay Co-ordination Using Support Vector Machines in Power Transmission System

In this paper, a new approach to enhance the transmission system distance relay co-ordination is presented. The approach depends on the apparent impedance loci seen by the distance relay during all possible disturbances. In a distance relay, the impedance loci seen at the relay location is obtained by extensive transient stability studies. Support vector machines (SVMs), a class of patterns classifiers are used in discriminating zone settings (zone-1, zone-2 and zone-3) using the signals to be used by the relay. Studies on a sample 9-bus are presented for illustrating the proposed scheme.

Minimization of Incompletely Specified Sequential Machines

A simple yet efficient method for the minimization of incompletely specified sequential machines (ISSMs) is proposed. Precise theorems are developed, as a consequence of which several compatibles can be deleted from consideration at the very first stage in the search for a minimal closed cover. Thus, the computational work is significantly reduced. Initial cardinality of the minimal closed cover is further reduced by a consideration of the maximal compatibles (MC's) only; as a result the method converges to the solution faster than the existing procedures. "Rank" of a compatible is defined. It is shown that ordering the compatibles, in accordance with their rank, reduces the number of comparisons to be made in the search for exclusion of compatibles. The new method is simple, systematic, and programmable. It does not involve any heuristics or intuitive procedures. For small- and medium-sized machines, it canle used for hand computation as well. For one of the illustrative examples used in this paper, 30 out of 40 compatibles can be ignored in accordance with the proposed rules and the remaining 10 compatibles only need be considered for obtaining a minimal solution.

State Minimization of Incompletely Specified Sequential Machines

A simple procedure for the state minimization of an incompletely specified sequential machine whose number of internal states is not very large is presented. It introduces the concept of a compatibility graph from which the set of maximal compatibles of the machine can be very conveniently derived. Primary and secondary implication trees associated with each maximal compatible are then constructed. The minimal state machine covering the incompletely specified machine is then obtained from these implication trees.

What are the driving factors influencing the size distribution of airborne synthetic clay particles emitted from a jet milling process?

In the field of workplace air quality, measuring and analyzing the size distribution of airborne particles to identify their sources and apportion their contribution has become widely accepted, however, the driving factors that influence this parameter, particularly for nanoparticles (< 100 nm), have not been thoroughly determined. Identification of driving factors, and in turn, general trends in size distribution of emitted particles would facilitate the prediction of nanoparticles’ emission behavior and significantly contribute to their exposure assessment. In this study, a comprehensive analysis of the particle number size distribution data, with a particular focus on the ultrafine size range of synthetic clay particles emitted from a jet milling machine was conducted using the multi-lognormal fitting method. The results showed relatively high contribution of nanoparticles to the emissions in many of the tested cases, and also, that both surface treatment and feed rate of the machine are significant factors influencing the size distribution of the emitted particles of this size. In particular, applying surface treatments and increasing the machine feed rate have the similar effect of reducing the size of the particles, however, no general trend was found in variations of size distribution across different surface treatments and feed rates. The findings of our study demonstrate that for this process and other activities, where no general trend is found in the size distribution of the emitted airborne particles due to dissimilar effects of the driving factors, each case must be treated separately in terms of workplace exposure assessment and regulations.