A new method to warm up lubricating oil to improve the fuel efficiency during cold start

Cold start driving cycles exhibit an increase in friction losses due to the low temperatures of metal and media compared to normal operating engine conditions. These friction losses are responsible for up to 10% penalty in fuel economy over the official drive cycles like the New European Drive Cycle (NEDC), where the temperature of the oil even at the end of the 1180 s of the drive cycle is below the fully warmed up values of between 100°C and 120°C. At engine oil temperatures below 100°C the water from the blow by condensates and dilutes the engine oil in the oil pan which negatively affects engine wear. Therefore engine oil temperatures above 100°C are desirable to minimize engine wear through blow by condensate. The paper presents a new technique to warm up the engine oil that significantly reduces the friction losses and therefore also reduces the fuel economy penalty during a 22°C cold start NEDC. Chassis dynamometer experiments demonstrated fuel economy improvements of over 7% as well as significant emission reductions by rapidly increasing the oil temperature. Oil temperatures were increased by up to 60°C during certain parts of the NEDC. It is shown how a very simple sensitivity analysis can be used to assess the relative size or efficiency of different heat transfer passes and the resulting fuel economy improvement potential of different heat recovery systems system. Due to its simplicity the method is very fast to use and therefore also very cost effective. The method demonstrated a very good correlation for the fuel consumption within ±1% compared to measurements on a vehicle chassis roll.

Adaptive cruise control look-ahead system for energy management of vehicles

Cruise control in motor vehicles enhances safe and efficient driving by maintaining a constant speed at a preset level. Adaptive Cruise Control (ACC) is the latest development in cruise control. It controls engine throttle position and braking to maintain a safe distance behind a vehicle in front by responding to the speed of this vehicle, thus providing a safer and more relaxing driving environment. ACC can be further developed by including the look-ahead method of predicting environmental factors such as wind speed and road slope. The conventional analytical control methods for adaptive cruise control can generate good results; however they are difficult to design and computationally expensive. In order to achieve a robust, less computationally expensive, and at the same time more natural human-like speed control, intelligent control techniques can be used. This paper presents an Adaptive Neuro-Fuzzy Inference System (ANFIS) based on ACC systems that reduces the energy consumption of the vehicle and improves its efficiency. The Adaptive Cruise Control Look-Ahead (ACC-LA) system works as follows: It calculates the energy consumption of the vehicle under combined dynamic loads like wind drag, slope, kinetic energy and rolling friction using road data, and it includes a look-ahead strategy to predict the future road slope. The cruise control system adaptively controls the vehicle speed based on the preset speed and the predicted future slope information. By using the ANFIS method, the ACC-LA is made adaptive under different road conditions (slope angle and wind direction and speed). The vehicle was tested using the adaptive cruise control look-ahead energy management system, the results compared with the vehicle running the same test but without the adaptive cruise control look-ahead energy management system. The evaluation outcome indicates that the vehicle speed was efficiently controlled through the look-ahead methodology based upon the driving cycle, and that the average fuel consumption was reduced by 3%.

Modeling a dynamic data replication strategy to increase system availability in cloud computing environments

Failures are normal rather than exceptional in the cloud computing environments. To improve system avai-lability, replicating the popular data to multiple suitable locations is an advisable choice, as users can access the data from a nearby site. This is, however, not the case for replicas which must have a fixed number of copies on several locations. How to decide a reasonable number and right locations for replicas has become a challenge in the cloud computing. In this paper, a dynamic data replication strategy is put forward with a brief survey of replication strategy suitable for distributed computing environments. It includes: 1) analyzing and modeling the relationship between system availability and the number of replicas; 2) evaluating and identifying the popular data and triggering a replication operation when the popularity data passes a dynamic threshold; 3) calculating a suitable number of copies to meet a reasonable system byte effective rate requirement and placing replicas among data nodes in a balanced way; 4) designing the dynamic data replication algorithm in a cloud. Experimental results demonstrate the efficiency and effectiveness of the improved system brought by the proposed strategy in a cloud.

Assessing effects of diel period, gear selectivity and predation on patterns of microhabitat use by fish in a mangrove dominated system in SE Australia

The relative value of temperate mangroves to fish, and the processes driving patterns of microhabitat use within this habitat, are unknown. There are 3 quickly identifiable microhabitats within temperate Australian mangroves: (1) forest (the area of mangroves with trees); (2) pneumatophores (the area directly seaward of the forest without trees but with pneumatophores [aerial roots]); and (3) channel (the area directly seaward of the pneumatophores without gross structural attributes such as trees or pneumatophores). Duplicate fyke and gill nets were both initially used to sample fish in the 3 microhabitats described above. Sampling took place across the seaward edge of mangroves on 10 sampling occasions (5 night and 5 day), in a large estuarine system in SE Australia. Fish assemblages (693 fish from 20 species and 15 families) varied significantly (p < 0.05) between the forest and the channel, and between diel periods for each gear (net type), but there was little difference in the assemblage structure of fish between forest–pneumatophore or pneumatophore–channel microhabitats. Juvenile lifestages (61% of all fish) and commercially important taxa (76%) were common. Abundance, biomass and species richness of fish were generally lower in the forest than the other microhabitats, but this pattern varied significantly (p < 0.05) between diel periods, among sampling occasions, and with water depth. Highly quantitative pop nets provided a preliminary assessment of whether differential gear selectivity caused patterns between microhabitats, but less rich fish assemblages were again recorded in forests than in pneumatophores. The importance of predation in structuring fish assemblages across microhabitats was assessed by measuring survival of juvenile fish tethered in 3 predation treatments (predator exclusion, cage control, and uncaged). Survival rates were high across the predator treatments and did not vary among microhabitats. The variation in fish assemblages across microhabitats within mangroves was not consistent with a model of mangrove structure providing a refuge for juvenile fish from predation, but instead could indicate differences in efficiency of gear types among microhabitats and/or other ‘edge effect’-driven processes such as the provision of food and/or shelter.

Framework for a Residential Energy Information System (REMIS) to promote energy efficient behaviour in residential energy end users

Previous studies on residential energy end use behavior reported significant reduction in energy end use of 7% to 24% when feedback is used to modify behavior in an energy efficient manner. However, most feedback systems investigated in previous studies have not benefited from advanced information systems (IS). IS can shape energy efficiency behavior by providing real-time feedback on energy consumption, cost and environmental impact. Such systems represent a new and less-researched subfield of energy informatics. This paper provides a conceptual framework for showing the potential use of IS to modify residential energy use behavior towards better energy efficiency. The framework builds on research in residential energy end use, in particular energy end use behavioral model. It provides conceptual inputs for a blue-print to develop a residential energy management information system (REMIS) and also highlights the use of new information and communications technologies (ICT) that had not been widely used, setting the grounds for further research in this area.

A novel exhaust heat recovery system to reduce fuel consumption

Internal combustion engines release about 1/3 of the energy bound in the fuel as exhaust waste gas energy and another 1/3 energy is wasted through heat transfer into the ambient. On the other hand losses through friction are the third largest root cause for energy loss in internal combustion engines. During city driving frictional losses can be of the same size as the effective work, and during cold start these losses are even bigger. Therefore it is obvious to utilise wasted exhaust energy to warm up the engine oil directly. Frictional losses of any engine can be reduced during part load. Sensitivity analyses have been conducted for different concepts that utilise exhaust energy to reduce engine viscosity and friction. For a new system with an exhaust gas/oil heat exchanger the following benefits have been demonstrated:

• Fuel consumption reductions of over 7% measured as an average over 5 NEDC tests
compared to the standard system configuration.
• Significant reductions in exhaust emissions, mainly CO and NOx have been achieved
• Significantly higher oil temperatures during cold start indicate large potential to
reduce engine wear through reduced water condensation in the crankcase
• Fuel consumption reductions of further 3.3% to 4.6% compared to the 7% measured
over the NEDC test can be expected under real world customer usage conditions at
lower ambient temperatures.

Oil temperature measurements and analysis resulted in the idea of a novel system with further potential to reduce fuel consumption. This Oil Viscosity Energy Recovery System (OVER 7™) consists of 3 key features that add significant synergies if combined in a certain way: an oil warm up circuit/bypass, including oil pressure control and Exhaust Gas/Oil Heat Exchanger. The system separates the thermal inertias of the oil in the engine galleries and the oil pan, reduces hydraulic pumping losses, increases the heat transfer from the cylinder head to the oil, and utilises the exhaust heat to reduce oil friction.

The project demonstrated that sensitivity analysis is an important tool for the evaluation of different concepts. Especially for new concepts that include transient heat transfer such a qualitative approach in combination with accurate experiments and measurements can be faster and more efficient in leading to the desired improvements compared to time consuming detailed simulations.

Implementation of a quality care management system for patients with arthritis of the hip and knee

The Orthopaedic Unit of the Repatriation General Hospital (RGH) in Adelaide, South Australia has implemented a quality care management system for patients with arthritis of the hip and knee. The system not only optimises conservative management but ensures that joint replacement surgery is undertaken in an appropriate and timely manner. This new service model addresses identified barriers to service access and provides a comprehensive, coordinated strategy for patient management. Over 4 years the model has reduced waiting times for initial outpatient assessment from 8 to 3 months and surgery from 18 to 8 months, while decreasing length of stay from 6.3 to 5.3 days for hips and 5.8 to 5.3 days for knees. The service reforms have been accompanied by positive feedback from patients and referring general practitioners in relation to the improved coordination of care and enhanced efficiency in service delivery.

What is known about the topic? Several important initiatives both overseas and within Australia have contributed significantly to the development of this model of care. These include the UK National Health Service ‘18 weeks’ Project, the Western Canada Waiting List Project, the New Zealand priority criteria project, the Queensland Health Orthopaedic Physiotherapy Screening Clinic, and most importantly the Melbourne Health–University of Melbourne Orthopaedic Waiting List Project where a wide range of models were explored across Victorian hospitals from 2005 and the Multi-Attribute Prioritisation Tool (MAPT) was developed, validated and tested. This project became the Osteoarthritis Hip and Knee Service (OAHKS) and was operationalised in the Victorian healthcare system from 2012. These initiatives examined and addressed various aspects of management systems for patients with arthritis of the hip and knee in their particular setting.

What does this paper add? The development of this system is an extension of what is already known and is the first to encompass a comprehensive and coordinated strategy across all stages of the care management pathway for this patient group. Their management extends from the initial referral to development and implementation of a management plan, including surgery if assessed as necessary and organisation of long-term post operative follow up as required. By detailing the elements, key processes and measurable outcomes of the service redesign this paper provides a model for other institutions to implement a similar initiative.

What are the implications for practitioners? An important aspect of the design process was practitioner acceptance and engagement and the ability to improve their capacity to deliver services within an efficient and effective model. Intrinsic to the model’s development was assessment of practitioner satisfaction. Data obtained including practitioner surveys indicated an increased level of both satisfaction with the redesigned management service, and confidence in it to deliver its intended improvements.

Reduced emergency calls and improved weekend discharge after introduction of a new electronic handover system

Objectives: To measure the frequency and content of electronic handover before and after implementation of the Blue BARRWUE handover system, and to measure its effect on patient safety and hospital efficiency over weekends.

Design, setting and participants: Point-prevalence study comparing outcomes for general medical inpatients present over weekends before implementation (1 May 2008 to 30 April 2009) and after implementation (1 May 2009 to 30 April 2010) of the Blue BARRWUE handover system at Geelong Hospital.

Intervention: Implementation of the Blue BARRWUE handover system and its components (updated working diagnosis, background, alerts, resuscitation status, requests, who to do what and when, updates and executable discharge plan).
Main outcome measures: Presence of any written handover notes or updated working diagnoses in the BOSSnet clinical information system, content of handover notes, frequency of weekend discharges and medical emergency team (MET) calls before and after implementation.

Results: In the 12 months before implementation of the Blue BARRWUE handover system, 976 patients (47.98%) had a handover note in BOSSnet, versus 1646 patients (95.09%) in the 12 months after implementation (P< 0.001; rate ratio [RR], 20.75; 95% CI, 16.33–26.44). Before implementation, 289 patients (14.21%) were discharged over weekends, versus 353 patients (20.39%) after implementation, (P < 0.001; RR, 1.44; 95% CI, 1.25–1.65). MET calls were made for 152 general medical patients before implementation (7.47%), versus 95 general medical patients (5.49%) after implementation (P= 0.01; RR, 0.73; 95% CI, 0.57–0.94).

Conclusions: The Blue BARRWUE system has sustainably improved written handover in our organisation and was associated with improvement in both patient safety and hospital efficiency.

Malwise-an effective and efficient classification system for packed and polymorphic malware

Signature-based malware detection systems have been a much used response to the pervasive problem of malware. Identification of malware variants is essential to a detection system and is made possible by identifying invariant characteristics in related samples. To classify the packed and polymorphic malware, this paper proposes a novel system, named Malwise, for malware classification using a fast application-level emulator to reverse the code packing transformation, and two flowgraph matching algorithms to perform classification. An exact flowgraph matching algorithm is employed that uses string-based signatures, and is able to detect malware with near real-time performance. Additionally, a more effective approximate flowgraph matching algorithm is proposed that uses the decompilation technique of structuring to generate string-based signatures amenable to the string edit distance. We use real and synthetic malware to demonstrate the effectiveness and efficiency of Malwise. Using more than 15,000 real malware, collected from honeypots, the effectiveness is validated by showing that there is an 88 percent probability that new malware is detected as a variant of existing malware. The efficiency is demonstrated from a smaller sample set of malware where 86 percent of the samples can be classified in under 1.3 seconds.

Neural network and interval type-2 fuzzy system for stock price forecasting

Stock price forecast has long been received special attention of investors and financial institutions. As stock prices are changeable over time and increasingly uncertain in modern financial markets, their forecasting becomes more important than ever before. A hybrid approach consisting of two components, a neural network and a fuzzy logic system, is proposed in this paper for stock price prediction. The first component of the hybrid, i.e. a feedforward neural network (FFNN), is used to select inputs that are highly relevant to the dependent variables. An interval type-2 fuzzy logic system (IT2 FLS) is employed as the second component of the hybrid forecasting method. The IT2 FLS’s parameters are initialized through deployment of the k-means clustering method and they are adjusted by the genetic algorithm. Experimental results demonstrate the efficiency of the FFNN input selection approach as it reduces the complexity and increase the accuracy of the forecasting models. In addition, IT2 FLS outperforms the widely used type-1 FLS and FFNN models in stock price forecasting. The combination of the FFNN and the IT2 FLS produces dominant forecasting accuracy compared to employing only the IT2 FLSs without the FFNN input selection.

An ant colony system based on the physarum network

The Physarum Network model exhibits the feature of important pipelines being reserved with the evolution of network during the process of solving a maze problem. Drawing on this feature, an Ant Colony System (ACS), denoted as PNACS, is proposed based on the Physarum Network (PN). When updating pheromone matrix, we should update both pheromone trails released by ants and the pheromones flowing in a network. This hybrid algorithm can overcome the low convergence rate and local optimal solution of ACS when solving the Traveling Salesman Problem (TSP). Some experiments in synthetic and benchmark networks show that the efficiency of PNACS is higher than that of ACS. More important, PNACS has strong robustness that is very useful for solving a higher dimension TSP.

A hierarchical cloud pricing system

Cloud computing is experiencing phenomenal growth and there are now many vendors offering their cloud services. In cloud computing, cloud providers cooperate together to offer their computing resource as a utility and software as a service to customers. The demands and the price of cloud service should be negotiated between providers and users based on the Service Level Agreement (SLA). In order to help cloud providers achieving an agreeable price for their services and maximizing the benefits of both cloud providers and clients, this paper proposes a cloud pricing system consisting of hierarchical system, M/M/c queuing model and pricing model. Simulation results verify the efficiency of our proposed system.

Integration of resident's energy costs in short stay accommodation billing system

This paper presents an energy management software package and the supporting energy information automation system to enable the short stay accommodation industry to determine actual residents' energy consumption. The proposed energy management system is used to develop a 'novel deal' method in short stay accommodation based on integration of the room level energy costs into the billing system. This system has the potential to increase energy efficiency in the short stay accommodation industry by actively engaging the residents in the energy saving process. The system is economically and environmentally sustainable and can achieve a high level of energy efficiency with low expenses. The proposed model is also effective for carbon mitigation, and offers a value proposition for all the parties in the short stay accommodation industry, including owners and residents. The paper presents a software system to capture room level energy consumption information and to present the detail of consumed energy information in the resident's accommodation bill. The presented information includes energy consumption profile, the greenhouse gas emission profile, and the cost associated to the energy related services.

Does coloniality improve foraging efficiency and nestling provisioning? A field experiment in the wild Zebra Finch

The foraging benefits of coloniality, whereby colony members exchange information about food location, have been suggested as a primary factor influencing the evolution of coloniality. However, despite its longstanding popularity, this hypothesis has rarely been tested experimentally. Here, we conducted a field experiment in the wild Zebra Finch Taeniopygia guttata to test whether colonial birds are better at finding food than solitary individuals. We manipulated food patch location and directly measured foraging activity of many colonial and solitary parents at those patches using an electronic monitoring system. We provided nesting sites in excess to alleviate nest site competition and manipulated brood size to eliminate the possible correlation between brood size, nesting density, and individual quality (including foraging activity). We found that solitary birds found experimental food patches first, closely followed by colonial birds. Moreover, solitary parents adjusted the amount of food per nestling to experimental brood size, whereas colonial parents did not, although overall, nestlings were fed more per capita in colonial than in solitary nests. In addition, brood size and, to a lesser extent, nesting density negatively affected nestling growth. Therefore, with the effect of provisioning rate, sibling competition, and cost of coloniality combined, nestling mass was not affected by the brood manipulation in solitary nests, whereas nestlings were lighter in enlarged than in reduced broods in colonies. Our results therefore suggest that individuals settling in solitary nests were intrinsically better foragers and more optimal parents. While they do not invalidate the possibility of information transfer at colonies, our findings highlight the importance of considering settlement bias in future studies and add to the existing evidence that the effects of nesting density on fitness are both complex and multiple.