Analysis of environmental efficiency variation : a materials balance approach

Recent literature has argued that environmental efficiency (EE), which is built on the materials balance (MB) principle, is more suitable than other EE measures in situations where the law of mass conversation regulates production processes. In addition, the MB-based EE method is particularly useful in analysing possible trade-offs between cost and environmental performance. Identifying determinants of MB-based EE can provide useful information to decision makers but there are very few empirical investigations into this issue. This article proposes the use of data envelopment analysis and stochastic frontier analysis techniques to analyse variation in MB-based EE. Specifically, the article develops a stochastic nutrient frontier and nutrient inefficiency model to analyse determinants of MB-based EE. The empirical study applies both techniques to investigate MB-based EE of 96 rice farms in South Korea. The size of land, fertiliser consumption intensity, cost allocative efficiency, and the share of owned land out of total land are found to be correlated with MB-based EE. The results confirm the presence of a trade-off between MB-based EE and cost allocative efficiency and this finding, favouring policy interventions to help farms simultaneously achieve cost efficiency and MP-based EE.

Improving the efficiency of high power piezoelectric transducers for industrial applications

Most high-power ultrasound applications are driven by two-level inverters. However, the broad spectral content of the two-level pulse results in undesired harmonics that can decrease the performance of the system significantly. On the other hand, it is crucial to excite the piezoelectric devices at their main resonant frequency in order to have maximum energy conversion. Therefore a high-quality, low-distorted power signal is needed to excite the high-power piezoelectric transducer at its resonant frequency. This study proposes an efficient approach to develop the performance of high-power ultrasonic applications using multilevel inverters along with a frequency estimation algorithm. In this method, the resonant frequencies are estimated based on relative minimums of the piezoelectric impedance frequency response. The algorithm follows the resonant frequency variation and adapts the multilevel inverter reference frequency to drive an ultrasound transducer at high power. Extensive simulation and experimental results indicate the effectiveness of the proposed approach.

Application of multi-criteria decision making methods to compression ignition engine efficiency and gaseous, particulate and greenhouse gas emissions

Compression ignition (CI) engine design is subject to many constraints which presents a multi-criteria optimisation problem that the engine researcher must solve. In particular, the modern CI engine must not only be efficient, but must also deliver low gaseous, particulate and life cycle greenhouse gas emissions so that its impact on urban air quality, human health, and global warming are minimised. Consequently, this study undertakes a multi-criteria analysis which seeks to identify alternative fuels, injection technologies and combustion strategies that could potentially satisfy these CI engine design constraints. Three datasets are analysed with the Preference Ranking Organization Method for Enrichment Evaluations and Geometrical Analysis for Interactive Aid (PROMETHEE-GAIA) algorithm to explore the impact of 1): an ethanol fumigation system, 2): alternative fuels (20 % biodiesel and synthetic diesel) and alternative injection technologies (mechanical direct injection and common rail injection), and 3): various biodiesel fuels made from 3 feedstocks (i.e. soy, tallow, and canola) tested at several blend percentages (20-100 %) on the resulting emissions and efficiency profile of the various test engines. The results show that moderate ethanol substitutions (~20 % by energy) at moderate load, high percentage soy blends (60-100 %), and alternative fuels (biodiesel and synthetic diesel) provide an efficiency and emissions profile that yields the most “preferred” solutions to this multi-criteria engine design problem. Further research is, however, required to reduce Reactive Oxygen Species (ROS) emissions with alternative fuels, and to deliver technologies that do not significantly reduce the median diameter of particle emissions.

Scaffold percolative efficiency : in vitro evaluation of the structural criterion for electrospun mats

Fibrous scaffolds of engineered structures can be chosen as promising porous environments when an approved criterion validates their applicability for a specific medical purpose. For such biomaterials, this paper sought to investigate various structural characteristics in order to determine whether they are appropriate descriptors. A number of poly(3-hydroxybutyrate) scaffolds were electrospun; each of which possessed a distinguished architecture when their material and processing conditions were altered. Subsequent culture of mouse fibroblast cells (L929) was carried out to evaluate the cells viability on each scaffold after their attachment for 24 h and proliferation for 48 and 72 h. The scaffolds’ porosity, pores number, pores size and distribution were quantified and none could establish a relationship with the viability results. Virtual reconstruction of the mats introduced an authentic criterion, “Scaffold Percolative Efficiency” (SPE), with which the above descriptors were addressed collectively. It was hypothesized to be able to quantify the efficacy of fibrous scaffolds by considering the integration of porosity and interconnectivity of the pores. There was a correlation of 80% as a good agreement between the SPE values and the spectrophotometer absorbance of viable cells; a viability of more than 350% in comparison to that of the controls.

A note on the ‘Linsanity’ of measuring the relative efficiency of National Basketball Association guards

This note examines the productive efficiency of 62 starting guards during the 2011/12 National Basketball Association (NBA) season. This period coincides with the phenomenal and largely unanticipated performance of New York Knicks’ starting point guard Jeremy Lin and the attendant public and media hype known as Linsanity. We employ a data envelopment analysis (DEA) approach that includes allowance for an undesirable output, here turnovers per game, with the desirable outputs of points, rebounds, assists, steals and blocks per game and an input of minutes per game. The results indicate that depending upon the specification, between 29% and 42% of NBA guards are fully efficient, including Jeremy Lin, with a mean inefficiency of 3.7% and 19.2%. However, while Jeremy Lin is technically efficient, he seldom serves as a benchmark for inefficient players, at least when compared with established players such as Chris Paul and Dwayne Wade. This suggests the uniqueness of Jeremy Lin's productive solution and may explain why his unique style of play, encompassing individual brilliance, unselfish play and team leadership, is of such broad public appeal.

Increasing NH4+ retention efficiency of sandy soils by adding a modified kaolin material: Mesolite

Water and ammonium retention by sandy soils may be low and result in leaching of applied fertiliser. To increase water and nutrient retention, zeolite is sometimes applied as a soil ameliorant for high value land uses including turf and horticulture. We have used a new modified kaolin material (MesoLite) as a soil amendment to test the efficiency of NH4+ retention and compared the results with natural zeolite. MesoLite is made by caustic reaction of kaolin at temperature between 80-95°C; although it has a moderate surface area, its cation exchange capacity is very high;(SA=13m2/g,CEC=500meq/100g). A 13cm tall sand column filled with ~450g of sandy soil homogeneously mixed with 1, 2, 4, and 8g of MesoLite or natural zeolite per 1kg of soil was prepared. After saturation with local bore water, concentrated ammonium sulfate solution was injected at the base. Then, bore water was passed from bottom to top through the column at amounts up to 6 pore volumes and at a constant flow rate of 10ml/min using a peristaltic pump. Concentrations of leached NH4+ were determined using an AutoAnalyser. The concentration of NH4+ leached from the column with 0.4% MesoLite was greatly (90%) reduced relative to unamended soil. Under these conditions NH4+ retention by the soil-MesoLite mixture was 11.5 times more efficient than the equivalent soil-natural zeolite mixture. Glasshouse experiments conducted in a separate study show that NH4+ adsorbed by MesoLite is available to plants.

Measurement error of rearfoot kinematics during running between a 100Hz and 30Hz camera

Background: Measurement accuracy is critical for biomechanical gait assessment. Very few studies have determined the accuracy of common clinical rearfoot variables between cameras with different collection frequencies. Research question: What is the measurement error for common rearfoot gait parameters when using a standard 30Hz digital camera compared to 100Hz camera? Type of study: Descriptive. Methods: 100 footfalls were recorded from 10 subjects ( 10 footfalls per subject) running on a treadmill at 2.68m/s. A high-speed digital timer, accurate within 1ms served as an external reference. Markers were placed along the vertical axis of the heel counter and the long axis of the shank. 2D coordinates for the four markers were determined from heel strike to heel lift. Variables of interest included time of heel strike (THS), time of heel lift (THL), time to maximum eversion (TMax), and maximum rearfoot eversion angle (EvMax). Results: THS difference was 29.77ms (+/- 8.77), THL difference was 35.64ms (+/- 6.85), and TMax difference was 16.50ms (+/- 2.54). These temporal values represent a difference equal to 11.9%, 14.3%, and 6.6% of the stance phase of running gait, respectively. EvMax difference was 1.02 degrees (+/- 0.46). Conclusions: A 30Hz camera is accurate, compared to a high-frequency camera, in determining TMax and EvMax during a clinical gait analysis. However, relatively large differences, in excess of 12% of the stance phase of gait, for THS and THL variables were measured.

Suspected mechanisms in the cause of overuse running injuries : A clinical review

Context: Various epidemiological studies have estimated that up to 70% of runners sustain an overuse running injury each year. Although few overuse running injuries have an established cause, more than 80% of running-related injuries occur at or below the knee, which suggests that some common mechanisms may be at work. The question then becomes, are there common mechanisms related to overuse running injuries? Evidence Acquisition: Research studies were identified via the following electronic databases: MEDLINE, EMBASE PsycInfo, and CINAHL (1980–July 2008). Inclusion was based on evaluation of risk factors for overuse running injuries. Results: A majority of the risk factors that have been researched over the past few years can be generally categorized into 2 groups: atypical foot pronation mechanics and inadequate hip muscle stabilization. Conclusion: Based on the review of literature, there is no definitive link between atypical foot mechanics and running injury mechanisms. The lack of normative data and a definition of typical foot structure has hampered progress. In contrast, a large and growing body of literature suggests that weakness of hip-stabilizing muscles leads to atypical lower extremity mechanics and increased forces within the lower extremity while running.

IMO mandatory energy efficiency measures for international shipping : the first mandatory global greenhouse gas reduction instrument for an international industry

Bunker fuels used in the aviation and maritime sectors are responsible for nearly 10% of global greenhouse gas emissions.1 According to a scientific survey: ‘[s]hipping is estimated to have emitted 1,046 million tonnes of CO2 in 2007, which corresponds to 3.3% of the global emissions during 2007. International shipping is estimated to have emitted 870 million tonnes, or about 2.7% of the global emissions of CO2 in 2007’. The study also predicted that ‘by 2050, in the absence of policies, ship emissions may grow by 150% to 250% (compared to the emissions in 2007) as a result of the growth in shipping.’

Energy efficient virtual machine placement in data centers

Electricity cost has become a major expense for running data centers and server consolidation using virtualization technology has been used as an important technology to improve the energy efficiency of data centers. In this research, a genetic algorithm and a simulation-annealing algorithm are proposed for the static virtual machine placement problem that considers the energy consumption in both the servers and the communication network, and a trading algorithm is proposed for dynamic virtual machine placement. Experimental results have shown that the proposed methods are more energy efficient than existing solutions.

Efficiency of knowledge integration in enterprise systems implementation

Recent literature has emphasized the pivotal role of knowledge integration in Enterprise Systems (ES) success. This research-in-progress paper, building upon Knowledge Based Theory of the firm (KBT), examines the efficiency of knowledge integration in the context of ES implementation and identifies the factors contributing to its enhancement. The proposed model in this paper suggests that the efficiency of knowledge integration in an ES implementation process depends upon the level of common knowledge and the level of coordination in the ES adopting organization. It further suggests that the level of common knowledge can be enhanced by proper training, improving ES users’intrinsic and extrinsic motivations and business process modeling and the level of coordination can be improved by articulating a clear unified organizational goal for the ES adoption in the organization, forming a competent ES team, enhancing interdepartmental communication and the cross-functionality in the organization structure.

Composite SaaS resource management in cloud computing using evolutionary computation

Cloud computing is an emerging computing paradigm in which IT resources are provided over the Internet as a service to users. One such service offered through the Cloud is Software as a Service or SaaS. SaaS can be delivered in a composite form, consisting of a set of application and data components that work together to deliver higher-level functional software. SaaS is receiving substantial attention today from both software providers and users. It is also predicted to has positive future markets by analyst firms. This raises new challenges for SaaS providers managing SaaS, especially in large-scale data centres like Cloud. One of the challenges is providing management of Cloud resources for SaaS which guarantees maintaining SaaS performance while optimising resources use. Extensive research on the resource optimisation of Cloud service has not yet addressed the challenges of managing resources for composite SaaS. This research addresses this gap by focusing on three new problems of composite SaaS: placement, clustering and scalability. The overall aim is to develop efficient and scalable mechanisms that facilitate the delivery of high performance composite SaaS for users while optimising the resources used. All three problems are characterised as highly constrained, large-scaled and complex combinatorial optimisation problems. Therefore, evolutionary algorithms are adopted as the main technique in solving these problems. The first research problem refers to how a composite SaaS is placed onto Cloud servers to optimise its performance while satisfying the SaaS resource and response time constraints. Existing research on this problem often ignores the dependencies between components and considers placement of a homogenous type of component only. A precise problem formulation of composite SaaS placement problem is presented. A classical genetic algorithm and two versions of cooperative co-evolutionary algorithms are designed to now manage the placement of heterogeneous types of SaaS components together with their dependencies, requirements and constraints. Experimental results demonstrate the efficiency and scalability of these new algorithms. In the second problem, SaaS components are assumed to be already running on Cloud virtual machines (VMs). However, due to the environment of a Cloud, the current placement may need to be modified. Existing techniques focused mostly at the infrastructure level instead of the application level. This research addressed the problem at the application level by clustering suitable components to VMs to optimise the resource used and to maintain the SaaS performance. Two versions of grouping genetic algorithms (GGAs) are designed to cater for the structural group of a composite SaaS. The first GGA used a repair-based method while the second used a penalty-based method to handle the problem constraints. The experimental results confirmed that the GGAs always produced a better reconfiguration placement plan compared with a common heuristic for clustering problems. The third research problem deals with the replication or deletion of SaaS instances in coping with the SaaS workload. To determine a scaling plan that can minimise the resource used and maintain the SaaS performance is a critical task. Additionally, the problem consists of constraints and interdependency between components, making solutions even more difficult to find. A hybrid genetic algorithm (HGA) was developed to solve this problem by exploring the problem search space through its genetic operators and fitness function to determine the SaaS scaling plan. The HGA also uses the problem's domain knowledge to ensure that the solutions meet the problem's constraints and achieve its objectives. The experimental results demonstrated that the HGA constantly outperform a heuristic algorithm by achieving a low-cost scaling and placement plan. This research has identified three significant new problems for composite SaaS in Cloud. Various types of evolutionary algorithms have also been developed in addressing the problems where these contribute to the evolutionary computation field. The algorithms provide solutions for efficient resource management of composite SaaS in Cloud that resulted to a low total cost of ownership for users while guaranteeing the SaaS performance.

The use of an electrostatic lens to enhance the efficiency of the electrospinning process

Electrospun scaffolds manufactured using conventional electrospinning configurations have an intrinsic thickness limitation, due to a charge build-up at the collector. To overcome this limitation, an electrostatic lens has been developed that, at the same relative rate of deposition, focuses the polymer jet onto a smaller area of the collector, resulting in the fabrication of thick scaffolds within a shorter period of time. We also observed that a longer deposition time (up to 13 h, without the intervention of the operator) could be achieved when the electrostatic lens was utilised, compared to 9–10 h with a conventional processing set-up and also showed that fibre fusion was less likely to occur in the modified method. This had a significant impact on the mechanical properties, as the scaffolds obtained with the conventional process had a higher elastic modulus and ultimate stress and strain at short times. However, as the thickness of the scaffolds produced by the conventional electrospinning process increased, a 3-fold decrease in the mechanical properties was observed. This was in contrast to the modified method, which showed a continual increase in mechanical properties, with the properties of the scaffold finally having similar mechanical properties to the scaffolds obtained via the conventional process at longer times. This “focusing” device thus enabled the fabrication of thicker 3-dimensional electrospun scaffolds (of thicknesses up to 3.5 mm), representing an important step towards the production of scaffolds for tissue engineering large defect sites in a multitude of tissues.

A new efficiency model for a regenerative dynamometer

This paper presents two efficiency models for the regenerative dynamometer to be built at the University of Queensland. The models incorporate an accurate accounting of the losses associated with the regenerative dynamometer and the battery modelling technique used. In addition to the models the cycle and instantaneous efficiencies were defined for a regenerative system that requires a desired torque output. The simulation of the models allowed the instantaneous and cycle efficiencies to be examined. The results show the intended dynamometer machine has significant efficiency draw backs but incorporating field winding control, the efficiency can be improved.

A method of extracting switching loss from a high efficiency MOSFET based half bridge converter

The measurement of losses in high efficiency / high power converters is difficult. Measuring the losses directly from the difference between the input and output power results in large errors. Calorimetric methods are usually used to bypass this issue but introduce different problems, such as, long measurement times, limited power loss measurement range and/or large set up cost. In this paper the total losses of a converter are measured directly and switching losses are exacted. The measurements can be taken with only three multimeters and a current probe and a standard bench power supply. After acquiring two or three power loss versus output current sweeps, a series of curve fitting processes are applied and the switching losses extracted.