The role of visual complexity and prototypicality regarding first impression of websites: Working towards understanding aesthetic judgments

This paper experimentally investigates the role of visual complexity (VC) and prototypicality (PT) as design factors of websites, shaping users' first impressions by means of two studies. In the first study, 119 screenshots of real websites varying in VC (low vs. medium vs. high) and PT (low vs. high) were rated on perceived aesthetics. Screenshot presentation time was varied as a between-subject factor (50 ms vs. 500 ms vs. 1000 ms). Results reveal that VC and PT affect participants' aesthetics ratings within the first 50 ms of exposure. In the second study presentation times were shortened to 17, 33 and 50 ms. Results suggest that VC and PT affect aesthetic perception even within 17 ms, though the effect of PT is less pronounced than the one of VC. With increasing presentation time the effect of PT becomes as influential as the VC effect. This supports the reasoning of the information-processing stage model of aesthetic processing (Leder et al., 2004), where VC is processed at an earlier stage than PT. Overall, websites with low VC and high PT were perceived as highly appealing.     

Advanced control with parameter estimation of batch transesterification reactor

The objective of this work is to enhance the economic performance of a batch transesterification reactor producing biodiesel by implementing advanced, model based control strategies. To achieve this goal, a dynamic model of the batch reactor system is first developed by considering reaction kinetics, mass balances and heat balances. The possible plant-model mismatch due to inaccurate or uncertain model parameter values can adversely affect model based control strategies. Therefore, an evolutionary algorithm to estimate the uncertain parameters is proposed. It is shown that the system is not observable with the available measurements, and hence a closed loop model predictive control cannot be implemented on a real system. Therefore, the productivity of the reactor is increased by first solving an open-loop optimal control problem. The objective function for this purpose optimizes the concentration of biodiesel, the batch time and the heating and cooling rates to the reactor. Subsequently, a closed-loop nonlinear model predictive control strategy is presented in order to take disturbances and model uncertainties into account. The controller, designed with a reduced model, tracks an offline determined set-point reactor temperature trajectory by manipulating the heating and cooling mass flows to the reactor. Several operational scenarios are simulated and the results are discussed in view of a real application. With the proposed optimization and control strategy and no parameter mismatch, a revenue of 2.76 $ min⁻¹ can be achieved from the batch reactor. Even with a minor parameter mismatch, the revenue is still 2.01 $ min⁻¹. While these values are comparable to those reported in the literature, this work also accounts for the cost of energy. Moreover, this approach results in a control strategy that can be implemented on a real system with limited online measurements.     

Neural-swarm visual saliency for path following

This paper extends an existing saliency-based model for path detection and tracking so that the appearance of the path being followed can be learned and used to bias the saliency computation process. The goal is to reduce ambiguities in the presence of strong distractors. In both original and extended path detectors, neural and swarm models are layered in order to attain a hybrid solution. With generalisation to other tasks in mind, these detectors are presented as instances of a generic neural-swarm layered architecture for visual saliency computation. The architecture considers a swarm-based substrate for the extraction of high-level perceptual representations, given the low-level perceptual representations extracted by a neural-based substrate. The goal of this division of labour is to ensure parallelism across the vision system while maintaining scalability and tractability. The proposed model is shown to exhibit, at 20 Hz, a 98.67% success rate on a diverse data-set composed of 39 videos encompassing a total of 29,789 640 × 480 frames. An open source implementation of the model, fully encapsulated as a node of the Robotics Operating System (ROS), is available for download.     

Using electromyography responses to investigate the effects of the display type,viewing distance,and viewing time on visual fatigue

The rapid success of 3D display technology and daily accessibility to 3D images has greatly increased the interest in such applications for a wide range of fields. This paper compares the effects of watching movies with 2D and 3D displays depending on the viewing distance (3H vs. 6H, where H is the height of the screen) and viewing time to determine the visual fatigue using electromyography (EMG) in terms of the percentage of maximum voluntary contraction (%MVC) of the orbicularis oculi (OO) muscle activity and a subjective visual discomfort score. Twenty healthy male university students with a mean age of 27.7 ± 2.53 years participated in this study as volunteers. None had color blindness, and all had normal vision acuity. A mixed-measures design was performed. The results showed that the viewing time and distance had significant effects on the %MVC and OO muscle activity depending on the display type. Watching the 3D display from a short viewing distance produced significantly high visual fatigue compared to watching the 2D display from a short viewing distance. However, the 3D display seemed to be less stressful than the 2D display at long viewing distances.     

Free-living inferential modeling of blood glucose level using only noninvasive inputs

The goal of this work is to present a causation modeling methodology with the ability to accurately infer blood glucose levels using a large set of highly correlated noninvasive input variables over an extended period of time. These models can provide insight to improve glucose monitoring, and glucose regulation through advanced model-based control technologies. The efficacy of this approach is demonstrated using real data from a type 2 diabetic (T2D) subject collected under free-living conditions over a period of 25 consecutive days. The model was identified and tested using eleven variables that included three food variables as well as several activity and stress variables. The model was trained using 20 days of data and validated using 5 days of data. This gave a fitted correlation coefficient of 0.70 and an average absolute error (AAE) (i.e., the average of the absolute values for the measured glucose concentration minus modeled glucose concentration) of 13.3 mg/dL for the validation data. This AAE result was significantly better than the subject’s personal glucose meter AAE of 15.3 mg/dL for replicated measurements.     

Distance estimation with mixed real and virtual targets in stereoscopic displays

In this paper we investigated the accuracy of center-to-center distance perception in near field augmented reality visual targets viewed by stereoscopic glasses. One real and one virtual targets were presented in four layout or target orientations (two horizontal and two vertical, by altering the relative positions of real and virtual targets) at three different parallax conditions (on screen, 5 cm from screen and 10 cm from screen) and four levels of scaled between targets’ distance (10–20 cm, 20–30 cm, 30–40 cm and 40–50 cm). The result revealed overall underestimation with an accuracy of about 84%. Interestingly, it was noticed that the main effects of layout, parallax and center-to-center distance were significant. Generally, accuracy improves when targets put vertical, close to observers’ position and smaller separation of targets. Significant interactions among the three main factors were also reported. The results are of great importance as it provides guide for the developers to decide where to present targets depending on the need for relative accuracy of judgment. Some engineering implications of the result are also discussed in this paper.     

The effects of 0.2 Hz varying latency with 20–100 ms varying amplitude on simulator sickness in a helmet mounted display

The relationship between the occurrence of simulator sickness (SS) and varying latency in a helmet-mounted display (HMD) was explored in this study. Previous work has always considered latency to be a constant. The aim of this research was to determine if a latency that varied over time would impact the experience of SS for HMD users. An object location task was used while viewing real, live video scenes via HMD. A planned comparisons approach was utilized with four experimental conditions, 2 of them having constant latency (0 ms added to system baseline, 200 ms added to system baseline) and 2 of them having sinusoidally varying latency (100 ms amplitude at 0.2 Hz frequency, and 20–100 ms varying amplitude at 0.2 Hz frequency). These conditions allowed for the assessment of the effects of constant latency vs. varying latency on the experience of SS. The results indicated that a varying latency is associated with greater experience of SS among HMD users than constant latency. Results also indicated, as has other recent research, that added constant latency on its own does not appear to be associated with the experience of higher levels of SS in an HMD.     

Dynamic workforce allocation in a constrained flow shop with multi-agent system

The present work addresses the problem of real time workforce scheduling in assembly lines where the number of operators is less to the number of workstations.The problem is faced developing a two-steps procedure made of (i) a centralized scheduling based on a constraint optimization problem (COP) for initial operator scheduling, and (ii) a decentralized algorithm performed by a multiagent system (MAS) to manage workers in case of unforeseen events.In the proposed MAS architecture, Agents represent the operators trying to find local assignments for themselves. The system is validated with a simulation model and implemented with a hardware infrastructure in a real assembly line of electromechanical components. The main original contribution of the paper consists in proving – by means of both validation through a simulation model and test in a real assembly line of electromechanical components – that (1) multi-agent systems could be successfully adopted to solve a workforce scheduling problem, and (2) a combined approach consisting of centralized + distributed approach would provide better results compared with the application of one of the two approaches alone.     

Fuel efficient power management strategy for fuel cell hybrid powertrains

A real time control strategy for fuel cell hybrid vehicles is proposed. The objective is to reduce the hydrogen consumption by using an efficient power sharing strategy between the fuel cell system (FCS) and the energy buffer (EB). The energy buffer (battery or supercapacitor) is charge-sustained (no plug-in capabilities). The real time control strategy is derived from a non-causal optimization algorithm based on optimal control theory. The strategy is validated experimentally with a hardware-in-the-loop (HiL) test bench based on a 600 W fuel cell system.     

Minimum amount of time required to retrieve peripheral numeric information in augmented-reality systems using a colour sequential DLP display

In a typical environment for augmented reality, subjects were asked to detect visual information presented at 15–28° in the periphery of the visual field. Information was displayed tachistoscopically for 200, 300 and 600 ms. Popular low cost beamer producing colour breakup was used to present peripheral stimuli. We found that exposure time affects detectability of targets. By extrapolating our results we compute that for a 100% correct detection the stimulus must be displayed for at least 2 s. Age does not affect detectability.     

A 24-h forecast of ozone peaks and exceedance levels using neural classifiers and weather predictions

A neural network combined to a neural classifier is used in a real time forecasting of hourly maximum ozone in the centre of France, in an urban atmosphere. This neural model is based on the MultiLayer Perceptron (MLP) structure. The inputs of the statistical network are model output statistics of the weather predictions from the French National Weather Service. These predicted meteorological parameters are very easily available through an air quality network. The lead time used in this forecasting is (t + 24) h. Efforts are related to a regularisation method which is based on a Bayesian Information Criterion-like and to the determination of a confidence interval of forecasting. We offer a statistical validation between various statistical models and a deterministic chemistry-transport model. In this experiment, with the final neural network, the ozone peaks are fairly well predicted (in terms of global fit), with an Agreement Index = 92%, the Mean Absolute Error = the Root Mean Square Error = 15 μg m⁻³ and the Mean Bias Error = 5 μg m⁻³, where the European threshold of the hourly ozone is 180 μg m⁻³.To improve the performance of this exceedance forecasting, instead of the previous model, we use a neural classifier with a sigmoid function in the output layer. The output of the network ranges from [0,1] and can be interpreted as the probability of exceedance of the threshold. This model is compared to a classical logistic regression. With this neural classifier, the Success Index of forecasting is 78% whereas it is from 65% to 72% with the classical MLPs. During the validation phase, in the Summer of 2003, six ozone peaks above the threshold were detected. They actually were seven.Finally, the model called NEUROZONE is now used in real time. New data will be introduced in the training data each year, at the end of September. The network will be re-trained and new regression parameters estimated. So, one of the main difficulties in the training phase – namely the low frequency of ozone peaks above the threshold in this region – will be solved.     

Data driven nonparametric identification and model based control of glucose-insulin process in type 1 diabetics

Closed loop control of glucose homeostasis via subcutaneous insulin infusion and continuous glucose monitoring system can give better living to a type 1 diabetic patient. This paper deals with the real time implementation of internal model control (IMC) of subcutaneous insulin infusion. The model based control is applied on the nonparametric model of the patient identified in real time from input–output data. Meal simulation model of the glucose-insulin system of type 1 diabetic patient based on the work of Dalla Man et. al. is considered. This model is constructed in hardware platform that acts as the virtual patient. The data-driven nonparametric model of the virtual patient is identified in real time by computing Volterra kernels. The kernels are solved up to second order using recursive least squares (RLS) algorithm with short memory length of M = 2. The validation results of the identified model output and the actual output have shown good fit in both simulation and real time environments. The frequency domain kernels are used in internal model control to generate insulin dosage. The control algorithm is developed in simulation and implemented in real time with hardware in loop on dSPACE platform. The closed loop system yields good meal disturbance rejection, less undershoots, settling time and more profoundly smaller requirement of insulin infusion as compared to the earlier reported data.     

Colonic fold detection from computed tomographic colonography images using diffusion-FCM and level sets

Colon cancer is the second major cause of cancer related deaths in industrial nations. Computed tomographic colonography (CTC) has emerged in the last decade as a new less invasive colon diagnostic alternative to the usually practiced optical colonoscopy. The overall goal is to increase the effectiveness of virtual endoscopic navigation of the existing computer-aided detection (CAD) system. The colonic/haustral folds serve as important landmarks for various associated tasks in the virtual endoscopic navigation like prone–supine registration, colonic polyp detection and tenia coli extraction. In this paper, we present two different techniques, first in isolation and then in synergism, for the detection of haustral folds. Our input is volumetric computed tomographic colonography (CTC) images. The first method, which uses a combination of heat diffusion and fuzzy c-means algorithm (FCM), has a tendency of over-segmentation. The second method, which employs level sets, suffers from under-segmentation. A synergistic combination, where the output of the first is used as an input for the second, is shown to improve the segmentation quality. Experimental results are presented on digital colon phantoms as well as real patient scans. The combined method has a total erroneous (over-segmentation plus under-segmentation) detection of (6.5 ± 2)% of the total number of folds per colon as compared to (12.5 ± 5)% for the diffusion-FCM-based method and (11.5 ± 3)% for the level set-based method. The p-values obtained from the associated ANOVA tests indicate that the performance improvements are statistically significant.     

Algorithms for acoustic localization based on microphone array in service robotics

This paper deals with the development of acoustic source localization algorithms for service robots working in real conditions. One of the main utilizations of these algorithms in a mobile robot is that the robot can localize a human operator and eventually interact with him/herself by means of verbal commands. The location of a speaking operator is detected with a microphone array based algorithm; localization information is passed to a navigation module which sets up a navigation mission using knowledge of the environment map. In fact, the system we have developed aims at integrating acoustic, odometric and collision sensors with the mobile robot control architecture. Good performance with real acoustic data have been obtained using neural network approach with spectral subtraction and a noise robust voice activity detector. The experiments show that the average absolute localization error is about 40 cm at 0 dB and about 10 cm at 10 dB of SNR for the named localization. Experimental results describing mobile robot performance in a talker following task are reported.     

Computer screen photo-assisted detection of complementary DNA strands using a luminescent zwitterionic polythiophene derivative

The computer screen photo-assisted technique (CSPT), a practical method for the evaluation of assays using computer screens as light sources and web cameras as detectors, has been used to detect the attachment of complementary DNA strands (20-mer, 5′-CAT GAT TGA ACC ATC CAC CA-3′) to a complex of single DNA strands and a polythiophene derivative (poly(3-[(S)-5-amino-5-carboxyl-3-oxapentyl]-2,5-thiophenylene hydrochloride (POWT)). The complex is a highly sequence specific indicator, based on non-covalent coupling of DNA to a water-soluble, zwitterionic, electroactive and photoactive polymer able to produce a combined absorption-emission signal readable by CSPT.The observed CSPT signal retains key spectral features of the complex spectrum, distinguishing the DNA attachment, as well as other stimuli, such as pH regulation at concentrations of 30 μM POWT and 15 μM DNA. A CSPT time resolved (linked to temperatures between 8 and 18 °C) approach is demonstrated as a complementary source of discrimination and for testing the robustness of the achieved classification.     

A distributed optical fiber sensor for temperature detection in power cables

The power transfer capacity of an underground power cable is limited by high-temperature regions that occur along the cable. It is very difficult to determine and control these ‘hot spots’. Optimum use and temperature profile control of power cables before and during load transmission can be achieved with real-time processing of temperature data. There are various methods developed for this purpose such as conventional point temperature measurement method, where a large number of sensors and connectors are required, and methods based on mathematical models which can only approach real values by approximation.In this study, temperature detection in an XLPE insulated 154 kV power cable is performed using a distributed sensing method where the optical fiber itself behaves as a sensor. Therefore, there is no need for the devices of conventional method. Moreover, contrary to methods based on mathematical models, where it is difficult to predict environmental variations, this method considers the variations with a temperature resolution of ±1 °C. Distributed temperature sensing (DTS) method, detection system configuration and required system parameters are explained in the paper. Experimental results obtained for 126 and 412 m cables show a temperature resolution of ±1 °C and a spatial resolution of 1.22 m. Simulations for a 10 km cable are also given. Results show that DTS is a reliable method for both short and long range cable systems.     

Aviation emission inventory development and analysis

An up to date and accurate aviation emission inventory is a prerequisite for any detailed analysis of aviation emission impact on greenhouse gases and local air quality around airports. In this paper we present an aviation emission inventory using real time air traffic trajectory data. The reported inventory is in the form of a 4D database which provides resolution of 1° × 1° × 1000 ft for temporal and spatial emission analysis. The inventory is for an ongoing period of six months starting from October 2008 for Australian Airspace.In this study we show 6 months of data, with 492,936 flights (inbound, outbound and over flying). These flights used about 2515.83 kt of fuel and emitted 114.59 kt of HC, 200.95 kt of CO, 45.92 kt of NO_x, 7929.89 kt of CO₂, and 2.11 kt of SO_x. From the spatial analysis of emissions data, we found that the CO₂ concentration in some parts of Australia is much higher than other parts, especially in some major cities. The emission results also show that NO_x emission of aviation may have a significant impact on the ozone layer in the upper troposphere, but not in the stratosphere.It is expected that with the availability of this real time aviation emission database, environmental analysts and aviation experts will have an indispensable source of information for making timely decisions regarding expansion of runways, building new airports, applying route charges based on environmentally congested airways, and restructuring air traffic flow to achieve sustainable air traffic growth.     

Application of a modified GA,ACO and a random search procedure to solve the production scheduling of a case study bakery

Based on the constraints and frame conditions given by the real processes the production in bakeries can be modelled as a no-wait permutation flow-shop, following the definitions in scheduling theory. A modified genetic algorithm, ant colony optimization and a random search procedure were used to analyse and optimize the production planning of a bakery production line that processes 40 products on 26 production stages. This setup leads to 8.2 × 10⁴⁷ different possible schedules in a permutation flow-shop model and is thus not solvable in reasonable time with exact methods. Two objective functions of economical interest were analysed, the makespan and the total idle time of machines. In combination with the created model, the applied algorithms proved capable to provide optimized results for the scheduling operation within a predefined runtime of 15 min, reducing the makespan by up to 8.6% and the total idle time of machines by up to 23%.     

Lighting,font style,and polarity on visual performance and visual fatigue with electronic paper displays

Visual performance and visual fatigue of electronic paper displays (electrophoretic display and cholesteric liquid crystal display) under ambient illuminances and light sources were studied and compared with paper. Forty-eight participants participated in a character-search task in the experiment. The results showed that search speed depends on the illuminance but not light source. Search speed increased as illumination increased from 300 lx (45.6 sec), 700 lx (44.18 sec) to 1500 lx (43.24 sec). The effect of medium display and polarity on accuracy was also significant. Accuracy was greater for electrophoretic display and positive polarity. However, the effect of illuminance and light source on visual fatigue was not statistically significant. Based on the results of this study, it seems that E-paper displays may need greater illumination (700 lx or higher).     

A high-brightness diffractive stereoscopic display technology

In this research, the diffractive blazed grating was proposed to produce the stereoscopic effects that were traditionally generated by barrier grating through parallax barrier method. Three wavelengths, 596 nm, 554 nm and 450 nm, were chosen as the main light waves for three sub-pixels, RGB. Because the diffractive optical element was directly attached to the color filter of a MPEG-4 player (Motion Picture Experts Group Four Player, MPEG-4 player) panel, the stereoscopic image remained high brightness. Since lithography would be the most possible manufacturing method, multilevel approximation was to proceeded during simulation. From the simulated results of optical simulation software, LightTools, the RGB lights moved parallelly and consequently avoiding cross-talk.