Assessing the ‘system’ in safe systems-based road designs: Using cognitive work analysis to evaluate intersection designs

While a safe systems approach has long been acknowledged as the underlying philosophy of contemporary road safety strategies, systemic applications are sparse. This article argues that systems-based methods from the discipline of Ergonomics have a key role to play in road transport design and evaluation. To demonstrate, the Cognitive Work Analysis framework was used to evaluate two road designs – a traditional Melbourne intersection and a cut-through design for future intersections based on road safety safe systems principles. The results demonstrate that, although the cut-through intersection appears different in layout from the traditional intersection, system constraints are not markedly different. Furthermore, the analyses demonstrated that redistribution of constraints in the cut-through intersection resulted in emergent behaviour, which was not anticipated and could prove problematic. Further, based on the lack of understanding of emergent behaviour, similar design induced problems are apparent across both intersections. Specifically, incompatibilities between infrastructure, vehicles and different road users were not dealt with by the proposed design changes. The importance of applying systems methods in the design and evaluation of road transport systems is discussed.     

Using cognitive agents in social simulations

Multi-Agent-Based Social Simulation (MABS) is a paradigm devoted to using agents as the modelling metaphor to simulate autonomous entities in a social world composed of a number of independent and interacting entities. Such models try to reproduce real environments and situations of interest within such environments. Most MABS platforms used today (e.g. MASON, Repast, NetLogo) see agents as very simple entities. However, there are situations in which a more intelligent kind of agent is needed. For example, when a society of persons with different roles and high-level behaviours must be modelled. In this paper, we address how to incorporate agents with cognitive skills into MABS.     

Improving physicians' performance with a stroke CDSS: A cognitive fit design approach

A large body of evidence over many years suggests that clinical decision support systems (CDSSs) can be helpful in improving both clinical outcomes and adherence to evidence-based guidelines. CDSSs have however failed to show their effectiveness due to poor ease of use and integration within clinical workflows. This research therefore emphasizes a cognitive fit design approach to developing an effective CDSS to solve those issues. According to the cognitive fit theory CDSS should align with the problem and task representation in order to match the physician's mental model to reduce cognitive effort. Several guidelines based on the cognitive fit design are proposed. A stroke CDSS prototype following the design guidelines is developed to demonstrate its feasibility. The system usability test results showed that the developed stroke CDSS was acceptably accurate, able to lessen the cognitive effort as desired, and preferable for use due to the significant reduction in cognitive load. The developed artifact has shown the potential to benefit physicians. Finally, implications and conclusions are discussed.     

Bright light effects on ultradian rhythms in performance on hemisphere-specific tasks

Ultradian rhythms in indices of brain hemisphere activity and in cognitive performance have been found in numerous studies. Asymmetry of these rhythms with regard to phase and frequency have also been documented in some studies. There is some evidence that bright light can affect ultradian rhythms of arousal state and vigilance. A study on unilateral exposure to bright light has demonstrated more pronounced effects of bright light on the right hemisphere. The aim of this study was to examine whether daytime intermittent bright light could affect parameters of ultradian rhythms in performance speed on hemisphere-specific tasks, and whether the effect of bright light was symmetric for the rhythms in performance on hemisphere-specific tasks presented laterally. A counter-balanced, within-subject research design was applied. The performance of 15 participants on hemisphere-specific tasks exposed laterally was measured every 30 min starting at 08:00 h and ending at 20:30 h in intermittent bright light (IBL, pulses of 15 min of 4000 lux light regularly interspersed between 45 min of background light levels of 300 lux) and in ordinary room light (ORL) conditions (300 lux). Individual time series data were subjected to cosinor analysis. General linear model analyses (the factors were: level of processing, visual field, and the task) were performed on the rhythms’ parameters. There was a substantial lengthening of the rhythms’ periods in IBL conditions for performance speed on spatial tasks and an increase in amplitude of the rhythms of performance speed for spatial tasks in both visual fields and for verbal tasks in the left visual field in the IBL conditions when compared to the ORL conditions. The results showed that the schedule of light exposure affected ultradian rhythms of hemisphere-specific tasks differently and that the right hemisphere seems to be more “sensitive” to light than the left hemisphere.     

University students' cognitive performance under temperature cycles induced by direct load control events

As one of the most common strategies for managing peak electricity demand, direct load control (DLC) of air‐conditioners involves cycling the compressors on and off at predetermined intervals. In university lecture theaters, the implementation of DLC induces temperature cycles which might compromise university students' learning performance. In these experiments, university students' learning performance, represented by four cognitive skills of memory, concentration, reasoning, and planning, was closely monitored under DLC‐induced temperature cycles and control conditions simulated in a climate chamber. In Experiment 1 with a cooling set point temperature of 22°C, subjects’ cognitive performance was relatively stable or even slightly promoted by the mild heat intensity and short heat exposure resulting from temperature cycles; in Experiment 2 with a cooling set point of 24°C, subjects’ reasoning and planning performance observed a trend of decline at the higher heat intensity and longer heat exposure. Results confirm that simpler cognitive tasks are less susceptible to temperature effects than more complex tasks; the effect of thermal variations on cognitive performance follows an extended‐U relationship with performance being relatively stable across a range of temperatures. DLC appears to be feasible in university lecture theaters if DLC algorithms are implemented judiciously.     

Cognitive simulation as a tool for cognitive task analysis

Cognitive simulations are runnable computer programs that represent models of human cognitive activities. We show how one cognitive simulation built as a model of some of the cognitive processes involved in dynamic fault management can be used in conjunction with small-scale empirical data on human performance to uncover the cognitive demands of a task, to identify where intention errors are likely to occur, and to point to improvements in the person-machine system. The simulation, called Cognitive Environment Simulation or CES, has been exercised on several nuclear power plant accident scenarios. Here we report one case to illustrate how a cognitive simulation tool such as CES can be used to clarify the cognitive demands of a problem-solving situation as part of a cognitive task analysis.     

Soft decision cooperative spectrum sensing with noise uncertainty reduction

Cognitive radio (CR) is a potential strategy for opportunistic access of idle resources to solve the conflicts between spectrum scarcity and underutilization. Spectrum sensing (SS) constitutes the most critical part in CR systems since the CR needs to detect the presence of primary signals reliably and quickly. Energy detection (ED) based SS is considered as the most preferable SS technique due to its simplicity and applicability. However, it is influenced by the effect of noise uncertainty which highly degrades its sensing performance. Cooperative spectrum sensing (CSS) is also introduced to mitigate some sensing problems such as multipath fading, shadowing, and hidden node problems. In this paper, we propose an enhanced fusion center (FC) rule for soft decision CSS using ED, which highly alleviates the noise uncertainty effect and enhances the sensing performance of cognitive radio networks (CRNs). In the proposed fusion rule, to increase the probability of detection and decrease the probability of false alarm, two dynamic thresholds are utilized by the FC. These thresholds are toggled based on predicting the current activity of the primary user (PU), and their values are dynamically changed based on estimating the noise uncertainty factor of the collected energy measurements from the CRs. To effectively predict (estimate) the current PU activity (the noise uncertainty factor), simple successive averaging processes over the collected energy measurements (the estimated noise variances) are performed by the FC, respectively. Theoretical analysis is performed on the proposed fusion rule for soft decision CSS to evaluate its enhanced false alarm and detection probabilities using different data combining schemes. Performance evaluations are also investigated to confirm the theoretical claims and to prove the effectiveness of the proposed scheme over the conventional ED based soft decision CSS.     

Constellation expanded active interference cancellation technique for suppression of out-of-band radiation in OFDM based cognitive radios

Cognitive radio is a novel technology to address the problem of spectrum under-utilization, by allowing the secondary users to dynamically use the spectrum of the primary users. OFDM is a potential candidate for the physical layer of cognitive radio, due to its inherent features of spectrum shaping, spectrum analysis and robustness to multipath. OFDM based cognitive radio, however suffers from out-of-band radiation (OOBR). In cognitive radio, suppression of OOBR is much more important as the interference to the primary users needs to be kept to the minimum possible level. In the literature, time and frequency characteristics of the transmitted signal have been exploited to minimize the OOBR. In this paper, we investigate the possibility of combining merits of the constellation expansion (CE) technique and the active interference cancellation (AIC) technique for suppression of OOBR. We show through simulations that the joint technique based on CE and AIC achieves much better OOBR reduction, with a slight degradation in error performance.     

Large scale spectrum survey in rural and urban environments within the 50 MHz–6 GHz bands

In-depth spectrum measurement was conducted in rural and urban locations, covering 50 MHz–6 GHz bands, during the weekdays and weekends. A modified duty cycle metric is presented by introducing a space variable into the existing metrics available today. An adaptive energy detection threshold technique was employed, the results indicate the average spectral occupancy of 0.18%, and 5.08% in rural and urban locations respectively during weekdays and 1.45% on weekends for urban locations. Furthermore, short and long term temporal variations of the duty cycle for each of the bands were studied, and it was found that GSM 900 shows significant temporal variation when compared with GSM 1800. It was also found that the choice of the detection threshold would significantly affect the duty cycle as GSM 900 and 1800 give exponential decay with increase in detection threshold while TV band shows very sharp exponential decay which becomes invariant after −85 dBm.     

Frequency agility in cognitive radios: A new measurement algorithm for optimal operative frequency selection

The wide diffusion of multimedia services delivered also on mobile terminals (smart-phone, tablets and so on), is causing a fast and continuous increasing of spectrum usage demand. Nevertheless, several studies have demonstrated that portions of radio spectrum are not in use for significant periods of time. This waste of spectrum shows the necessity to design a more flexible way to manage this resource with respect to the traditional frequency allocation policy.In this context, cognitive radios play a crucial role, because they are thought to enable such flexible spectrum allocation by suitably changing their operating frequency without interfering with other transmitters. As a consequence, they have to implement a method to dynamically select the appropriate operating frequency based on the sensing of signals from other transmitters. This capability is usually called frequency agility.Several spectrum sensing methods have been proposed in literature, whereas few studies have been focused on the development of methods for satisfying the frequency agility capability.In this framework, the paper proposes a novel measurement algorithm able to meet those requirements. It is based on two sequential steps: the former performs a preliminary spectrum sensing aimed at excluding the frequency ranges surely occupied by primary users, while the latter performs a more refined analysis, restricted to frequency intervals not excluded by the previous stage, with the aim of selecting an operating frequency for the cognitive radio terminal that minimizes potential interferences with primary users. It has been designed for operating in scenarios involving signals based on OFDM or which present spectrum shapes and slopes similar to ones shown by OFDM.A key feature of the proposal is the ability to operate even in scenarios characterized by low signal-to-noise ratios as confirmed also by the experimental campaign.