8 research outputs found

    The Influence of Lighting Settings on Museum’s Brand Image and Human Satisfaction in Exhibition Halls Using Virtual Reality

    Get PDF
    This paper analyses the influence of museum lighting design on the brand image and human satisfaction inside exhibition halls, taking Birmingham museum and art gallery as the case study of this research focusing on the exhibition that included the ancient Egyptian displays. Four different generated lighting scenes using virtual reality were generated. The results showed that the lighting had an impact on the brand image and affect the willingness of people to revisit the museum and recommend it to family and friends. This research considers the museum’s visitors as active participants not just passive recipients of environmental stimuli. The research tried to provide a better understanding of how the exhibition environment in terms of lighting is perceived and provide further insight into how exhibition lighting design can enhance the visitor’s experience and create a brand image. According to the research results, visitors tend to be willing to return and stay longer in the presence of diverse and exciting lighting settings

    Energy harvesting and battery power based routing in wireless sensor networks

    No full text
    Wireless sensor networks (WSNs) are a collection of several small and inexpensive battery-powered nodes, commonly used to monitor regions of interests and to collect data from the environment. Several issues exist in routing data packets through WSN, but the most crucial problem is energy. There are a number of routing approaches in WSNs that address the issue of energy by the use of different energy-efficient methods. This paper, presents a brief summary of routing and related issues in WSNs. The most recent energy-efficient data routing approaches are reviewed and categorized based on their aims and methodologies. The traditional battery based energy sources for sensor nodes and the conventional energy harvesting mechanisms that are widely used to in energy replenishment in WSN are reviewed. Then a new emerging energy harvesting technology that uses piezoelectric nanogenerators to supply power to nanosensor; the type of sensors that cannot be charged by conventional energy harvesters are explained. The energy consumption reduction routing strategies in WSN are also discussed. Furthermore, comparisons of the variety of energy harvesting mechanisms and battery power routing protocols that have been discussed are presented, eliciting their advantages, disadvantages and their specific feature. Finally, a highlight of the challenges and future works in this research domain is presented

    A novel method to water level prediction using RBF and FFA

    No full text
    Water level prediction of rivers, especially in flood prone countries, can be helpful to reduce losses from flooding. A precise prediction method can issue a forewarning of the impending flood, to implement early evacuation measures, for residents near the river, when is required. To this end, we design a new method to predict water level of river. This approach relies on a novel method for prediction of water level named as RBF-FFA that is designed by utilizing firefly algorithm (FFA) to train the radial basis function (RBF) and (FFA) is used to interpolation RBF to predict the best solution. The predictions accuracy of the proposed RBF–FFA model is validated compared to those of support vector machine (SVM) and multilayer perceptron (MLP) models. In order to assess the models’ performance, we measured the coefficient of determination (R2), correlation coefficient (r), root mean square error (RMSE) and mean absolute percentage error (MAPE). The achieved results show that the developed RBF–FFA model provides more precise predictions compared to different ANNs, namely support vector machine (SVM) and multilayer perceptron (MLP). The performance of the proposed model is analyzed through simulated and real time water stage measurements. The results specify that the developed RBF–FFA model can be used as an efficient technique for accurate prediction of water stage of river

    Yersinia enterocolitica and Yersinia pseudotuberculosis

    No full text
    corecore