Consumers who don't want to look for information

A model to identify and classify consumers with high resistance to searching for information (HRSI) was developed and tested. We found that individuals with high levels of confidence about a purchase but who also ascribed low levels of personal importance to the transaction were significantly (p=.004) more likely to be HRSI. Using Multiple Discriminant Analysis, our model classified and predicted HRSI consumers well (p=.004, 57% above chance) but not low-resistance consumers (p=.6, 26.4% below chance).

Backward modelling and look-ahead fuzzy energy management controller for a parallel hybrid vehicle

This paper focuses on a parallel hybrid electric vehicle. It first develops a model for the vehicle using the backward-looking approach where the flow of energy starts from wheels and spreads towards engine and electric motor. Next, a fuzzy logic-based strategy is developed to control the operation of the vehicle. The objectives of the controller include managing the energy flow from engine and electric motor, controlling transmission ratio, adjusting speed, and sustaining battery's state of charge. The controller examines current vehicle speed, demand torque, slope difference, state of charge of battery, and engine and electric motor rotation speeds. Then, it determines the best values for continuous variable transmission ratio, speed, and torque. A slope window scheme is also developed to take into account the look-ahead slope information and determine the best vehicle speed for better fuel economy. The developed model and control strategy are simulated. The simulation results are presented and discussed. It is shown that the use of the proposed fuzzy controller reduces fuel consumption.

Don't look down

Musical composition recorded and output as a download album. The album features 16 tracks:
1. Entangled
2. Ambient thing
3. Alight
4. Sometimes
5. Late at night
6. Don't look down
7. Treasure
8. Relent
9. Absconding
10. Silently
11. Easy now
12. Baltic winter
13. Honeymoon
14. Lament
15. Reef knot
16. Yeah

Look-ahead intelligent energy management of a parallel hybrid electric vehicle

Improving fuel efficiency in vehicles can reduce the energy consumption concerns associated with operating the vehicles. This paper presents a model for a parallel hybrid electric vehicle. In the model, the flow of energy starts from wheels and spreads toward engine and electric motor. A fuzzy logic based control strategy is implemented for the vehicle. The controller manages the energy flow from the engine and the electric motor, controlling transmission ratio, adjusting speed, and sustaining battery's state of charge. The controller examines the vehicle speed, demand torque, slope difference, state of charge of battery, and engine and electric motor rotation speeds. It then determines the best values for continuous variable transmission ratio, speed, and torque. A slope window method is formed that takes into account the look-ahead slope information, and determines the best vehicle speed. The developed model and control strategy are simulated using real highway data relating to Nowra-Bateman Bay in Australia, and SAE Highway Fuel Economy Driving Schedule. The simulation results are presented and discussed. It is shown that the use of the proposed fuzzy controller reduces the fuel consumption of the vehicle.

A look-ahead road grade determination method for HEVs

This paper presents a look-ahead road grade determination method for use in energy management of hybrid electric vehicles. Data that is gathered from a digital map and vehicle sensors is used to predict the future road grade and longitudinal forces. The predicted information is employed to specify the near future traction force demand. A simulation is carried out using data associated with a 50 km section of a real highway for a typical vehicle. The results are presented and discussed.

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%.

Networking of Multimedia Women Event : beyond epsilon science - "where to look and how to realize new opportunities"

"Networking of Multimedia Women" event is a continuation of an on-going conversation in the multimedia research community and efforts by the ACM SIGMM to engage and promote female researchers in multimedia community, enable networking of junior and senior female researchers, and give insights towards successful professional careers based on examples. This year, the event will have a theme, called "Beyond Epsilon Science", where preeminent senior female researchers from academia, industry and government, Svetha Venkatesh, Nalini Venkatasubramanian, Dulce Ponceleon, Susanne Boll, and Maria Zemankova will present and discuss how to go beyond epsilon science, where to look for big ideas with high social impact, as well as how to obtain funding to realize these ideas, innovations and opportunities. Their current research projects and funding efforts, and their personal experiences will drive the event's discussions, awareness of major research and funding initiatives, answers to open questions and insights into successful professional careers.

Gaze behavior among experts and trainees during optic disc examination : does how we look affect what we see?

Purpose. The authors compared the visual gaze behaviors of glaucoma subspecialists with those of ophthalmology trainees during optic disc and retinal nerve fiber layer (RNFL) examination.

Methods. Seven glaucoma subspecialists and 23 ophthalmology trainees participated in the project. Participants were shown eight glaucomatous optic disc images with varied morphology. Eye movements during examination of the optic disc photographs were tracked. For each disc image, graders were asked to assign a presumptive diagnosis for probability of glaucoma. There was no time restriction.

Results. Overall, trainees spent more time looking at disc images than glaucoma subspecialists (21.3 [13.9–37.7] vs. 16.6 [12.7–19.7]) seconds; median [interquartile range (IQR)], respectively; P < 0.01) and had no systematic patterns of gaze behavior, and gaze behavior was unaltered by disc morphology or topographic cues of pathology. Experienced viewers demonstrated more systematic and ordered gaze behavior patterns and spent longer times observing areas with the greatest likelihood of pathology (superior and inferior poles of the optic nerve head and adjacent RNFL) compared with the trainees. For discs with focal pathology, the proportion of total time spent examining definite areas of pathology was 28.9% (22.4%–33.6%) for glaucoma subspecialists and 13.5% (12.2%–19.2%) for trainees (median [IQR]; P < 0.05). Furthermore, experts adapted their viewing habits according to disc morphology.

Conclusions. Glaucoma subspecialists adopt systematic gaze behavior when examining the optic nerve and RNFL, whereas trainees do not. It remains to be elucidated whether incorporating systematic viewing behavior of the optic disc and RNFL into teaching programs for trainees may expedite their acquisition of accurate and efficient glaucoma diagnosis skills.

A fresh look at the validity of diffusion equations for modelling phosphorescence imaging of biological tissue

Phosphorescence lifetime imaging has become a widely used technique for tomographic oxygen imaging. The conventional model used to characterize photon transport in phosphorescence imaging is two coupled diffusion equations. On the premise that the total energy of excitation and phosphorescence photon flows must be conserved, we derive the diffusion equations in phosphorescence imaging and show that there must be an additional term to account for the transport of phosphorescent photons. This additional term accounts for the transport of phosphorescence photon energy density due to its gradients. The significance of this term in modelling phosphorescence in biological tissue is assessed.