Retinoblastoma: Identifying the Diagnostic Signs for Early Treatment

Retinoblastoma is a rare but significant cause of childhood eye cancer world-wide. The prognosis depends upon early diagnosis and treatment but also upon accurate classification of the tumours. Unilateral incidence is normally non-hereditary compared with bilateral incidence where secondary tumours are more common. Survivorship is much better for unilateral compared with bilateral and trilateral retinoblastoma. Early signs are important to detect and photography can assist in identifying no return of “red-eye” during flash photography and yellow appearance of the tumour. Treatment options are discussed together with new psycho-oncology approaches that address potential trauma in the survivor as well as in the family of the survivor

Big data analytics:Computational intelligence techniques and application areas

Big Data has significant impact in developing functional smart cities and supporting modern societies. In this paper, we investigate the importance of Big Data in modern life and economy, and discuss challenges arising from Big Data utilization. Different computational intelligence techniques have been considered as tools for Big Data analytics. We also explore the powerful combination of Big Data and Computational Intelligence (CI) and identify a number of areas, where novel applications in real world smart city problems can be developed by utilizing these powerful tools and techniques. We present a case study for intelligent transportation in the context of a smart city, and a novel data modelling methodology based on a biologically inspired universal generative modelling approach called Hierarchical Spatial-Temporal State Machine (HSTSM). We further discuss various implications of policy, protection, valuation and commercialization related to Big Data, its applications and deployment

The effect of digital signage on shoppers' behavior: the role of the evoked experience

This paper investigates the role of digital signage as experience provider in retail spaces. The findings of a survey-based field experiment demonstrate that digital signage content high on sensory cues evokes affective experience and strengthens customers’ experiential processing route. In contrast, digital signage messages high on “features and benefits” information evoke intellectual experience and strengthen customers’ deliberative processing route. The affective experience is more strongly associated with the attitude towards the ad and the approach behavior towards the advertiser than the intellectual experience. The effect of an ad high on sensory cues on shoppers’ approach to the advertiser is stronger for first-time shoppers, and therefore important in generating loyalty. The findings indicate that the design of brand-related informational cues broadcast over digital in-store monitors affects shoppers’ information processing. The cues evoke sensory and affective experiences and trigger deliberative processes that lead to attitude construction and finally elicit approach behavior towards the advertisers

ANN for Parkinson’s Disease Prediction

Parkinson's Disease (PD) is a long-term degenerative disorder of the central nervous system that mainly affects the motor system. The symptoms generally come on slowly over time. Early in the disease, the most obvious are shaking, rigidity, slowness of movement, and difficulty with walking. Doctors do not know what causes it and finds difficulty in early diagnosing the presence of Parkinson’s disease. An artificial neural network system with back propagation algorithm is presented in this paper for helping doctors in identifying PD. Previous research with regards to predict the presence of the PD has shown accuracy rates up to 93% [1]; however, accuracy of prediction for small classes is reduced. The proposed design of the neural network system causes a significant increase of robustness. It is also has shown that networks recognition rates reached 100%

Referencial para a caracterização de websites de hotéis de acordo com as necessidades dos consumidores

Online presence is essential for tourism organisations, and the quality of websites can influence customers. In the case of hotels, there are many studies to evaluate website performance based on functionality, usability and other factors, much less on the amount of different information available to the consumer. In the near future by using Big Data it is expected that hotel websites will be dynamic, they will adapt themselves on-the-fly, showing personalized information to each consumer. Different consumers will have different websites (information? available) from the same hotel. This paper presents a framework for the characterisation of hotel websites, focusing on the amount of information available to the consumer in each website, which was applied in a case study during the last months of 2013 to the websites of five-star hotels that operate in the tourist region of the Algarve, Portugal. The framework allowed to identify a set of exhaustive indicators for hotel website characterisation, which were then grouped into ten fundamental information dimensions. These dimensions further fell into four dimension groups. Finally, it is presented and discussed quantitative and qualitative evaluations, that illustrates which indicators and dimensions are more often considered on hotel websites to satisfy the consumer?s information needs