The fickle nature of similarity change as a result of categorization

Several researchers have reported that learning a particular categorization leads to compatible changes in the similarity structure of the categorized stimuli. The purpose of this study is to examine whether different category structures may lead to greater or less corresponding similarity change. We created six category structures and examined changes in similarity within categories or between categories, as a result of categorization, in between-participant conditions. The best supported hypothesis was that the ease of learning a categorization affects change in within categories similarity, so that greater (within categories) similarity change was observed for category structures which were harder to learn

Aesthetic appeal influences visual search performance.

Aesthetic appeal of a visual image can influence performance in time-critical tasks, even if it is irrelevant to the task. This series of experiments examined whether aesthetic appeal can act as an object attribute that guides visual search. If appeal enhances the salience of the targets pre-attentively, then appealing icons would lead to more efficient searches than unappealing targets and, conversely, appeal of distractors would reduce search efficiency. Three experiments (N = 112) examined how aesthetic appeal influences performance in a classic visual search task. In each experiment, participants completed 320 visual search trials, with icons varying in rated aesthetic appeal and either visual complexity (Experiments 1 and 2) of concreteness (Experiment 3) among two, four, eight, or 11 distractor icons. While target appeal did not influence search efficiency it sped up search times in all three experiments: appealing targets led to faster response time (RT) than unappealing targets across all experiments, and compared to neutral distractors, appealing distractors slowed search RT down. These findings are the first to show that an object's aesthetic appeal influences visual search performance

Mood moderates the effect of aesthetic appeal on performance

Aesthetically appealing stimuli can improve performance in demanding target localisation tasks compared to unappealing stimuli. Two search-and-localisation experiments were carried out to examine the possible underlying mechanism mediating the effects of appeal on performance. Participants (N = 95) were put in a positive or negative mood prior to carrying out a visual target localisation task with appealing and unappealing targets. In both experiments, positive mood initially led to faster localisation of appealing compared to unappealing stimuli, while an advantage for appealing over unappealing stimuli emerged over time in negative mood participants. The findings are compatible with the idea that appealing stimuli may be inherently rewarding, with aesthetic appeal overcoming the detrimental effects of negative mood on performance

Design standards for icons: The independent role of aesthetics, visual complexity and concreteness in icon design and icon understanding

Icons play an important role in modern interfaces and therefore recent empirical research has focused on enhancing icon processing — that is, icon perception and icon function understanding. However, in existing sets, icons vary simultaneously across different icon characteristics, confusing the contribution of each to icon processing. We developed icon design principles for aesthetics, complexity, and concreteness, and used them to create 64 icons that varied independently along each characteristic. Participants reported the icon function and rated each icon in terms of aesthetics, complexity and concreteness. The manipulated characteristics had independent effects on icon processing, with two exceptions, for which we propose evidence-based solutions. Based on these findings we propose guidelines for designing icons for research purposes

The relative contribution of shape and colour to object memory

The current studies examined the relative contribution of shape and colour in object representations in memory. A great deal of evidence points to the significance of shape in object recognition, with the role of colour being instrumental under certain circumstances. A key but yet unanswered question concerns the contribution of colour relative to shape in mediating retrieval of object representations from memory. Two experiments (N=80) used a new method to probe episodic memory for objects and revealed the relative contribution of colour and shape in recognition memory. Participants viewed pictures of objects from different categories, presented one at a time. During a practice phase, participants performed yes/no recognition with some of the studied objects and their distractors. Unpractised objects shared shape only (Rp–Shape), colour only (Rp–Colour), shape and colour (Rp–Both), or neither shape nor colour (Rp–Neither), with the practised objects. Interference effects in memory between practised and unpractised items were revealed in the forgetting of related unpractised items – retrieval-induced forgetting. Retrieval-induced forgetting was consistently significant for Rp–Shape and Rp–Colour objects. These findings provide converging evidence that colour is an automatically encoded object property, and present new evidence that both shape and colour act simultaneously and effectively to drive retrieval of objects from long-term memory

Fault diagnosis for uncertain networked systems

Fault diagnosis has been at the forefront of technological developments for several decades. Recent advances in many engineering fields have led to the networked interconnection of various systems. The increased complexity of modern systems leads to a larger number of sources of uncertainty which must be taken into consideration and addressed properly in the design of monitoring and fault diagnosis architectures. This chapter reviews a model-based distributed fault diagnosis approach for uncertain nonlinear large-scale networked systems to specifically address: (a) the presence of measurement noise by devising a filtering scheme for dampening the effect of noise; (b) the modeling of uncertainty by developing an adaptive learning scheme; (c) the uncertainty issues emerging when considering networked systems such as the presence of delays and packet dropouts in the communication networks. The proposed architecture considers in an integrated way the various components of complex distributed systems such as the physical environment, the sensor level, the fault diagnosers, and the communication networks. Finally, some actions taken after the detection of a fault, such as the identification of the fault location and its magnitude or the learning of the fault function, are illustrated

The modulation of inhibition of return by object internal structure Implications for theories of object-based attention and object shape representation

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