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- Artificial intelligence applications and innovations: day-to-day life impactPublication . Rodrigues, João; Cardoso, Pedro; Chinnici, MartaThe idea of an intelligent machine has fascinated humans for centuries. But what is intelligence? Some define it as the capacity for learning, reasoning, understanding or, from a different perspective, the aptitude to grasp truths, relationships, facts, or meanings. All these perspectives require the capacity to acquire data from the surrounding world and, possibly, act over that environment. In short, the building of more or less autonomous agents, served with sensors and actuators, capable of learning and producing educated answers has been long foreseen. New trends in intelligente systems comprise, among other aspects, pervasive robotization, ubiquitous online data access, empowered edge computing, smart spaces, and digital ethics. These trends build the research on “Artificial Intelligence Applications and Innovation”, impacting our day-to-day life, our cities, and even our free time. Nevertheless, artificial intelligence (AI) is still closely associated with some popular misconceptions that cause the public to either have unrealistic fears about it or to have unrealistic expectations about how it will change our workplace and life in general. It is important to show that such fears are unfounded and that new trends, innovations, technologies, and smart systems will be able to improve the way we live, benefiting society without replacing humans in their core activities.
- Mobile five senses augmented reality system: technology acceptance studyPublication . Rodrigues, João; Ramos, Celia; Pereira, Joao A. R.; Sardo, Joao D. P.; Cardoso, PedroThe application of the most recent technologies is fundamental to add value to tourism experiences, as well as in other economic sectors. Mobile Five Senses Augmented Reality (M5SAR) system is a mobile guide instrument for cultural, historical, and museum events. In order to realize the proclaimed five senses, the system has two main modules: a (i) mobile application which deals mainly with the senses of sight and hearing, using for that the mobile device camera to recognize and track on-the-fly (museum's) objects and give related information about them; and a (ii) portable device capable of enhancing the augmented reality (AR) experience to the full five senses through the stimulus of touch, taste, and smell, by associating itself to the users' smartphone or tablet. This paper briefly presents the system's architecture but, the main focus is on the analysis of the users' acceptance for this technology, namely the AR (software) application, and its integration with the (hardware) device to achieve the five senses AR. Results show that social influence, effort expectancy, and facilitating conditions are the key constructs that drive the users to accept and M5SAR's technology.
- A decision-support system to Analyse Customer Satisfaction Applied to a Tourism Transport ServicePublication . Ramos, Celia; Cardoso, Pedro; Fernandes, Hortênsio C. L.; Rodrigues, JoãoDue to the perishable nature of tourist products, which impacts supply and demand, the possibility of analysing the relationship between customers’ satisfaction and service quality can contribute to increased revenues. Machine learning techniques allow the analysis of how these services can be improved or developed and how to reach new markets, and look for the emergence of ideas to innovate and improve interaction with the customer. This paper presents a decision-support system for analysing consumer satisfaction, based on consumer feedback from the customer’s experience when transported by a transfer company, in the present case working in the Algarve region, Portugal. The results show how tourists perceive the service and which factors influence their level of satisfaction and sentiment. One of the results revealed that the first impression associated with good news is what creates the most value in the experience, i.e., “first impressions matter”..
- Framework for a Hospitality Big Data Warehouse: The Implementation of an Efficient Hospitality Business Intelligence SystemPublication . Ramos, Celia; Martins, Daniel; Serra, Francisco; Lam, Roberto; Cardoso, Pedro; Correia, Marisol; Rodrigues, Joãoorder to increase the hotel's competitiveness, to maximize its revenue, to meliorate its online reputation and improve customer relationship, the information about the hotel's business has to be managed by adequate information systems (IS). Those IS should be capable of returning knowledge from a necessarily large quantity of information, anticipating and influencing the consumer's behaviour. One way to manage the information is to develop a Big Data Warehouse (BDW), which includes information from internal sources (e.g., Data Warehouse) and external sources (e.g., competitive set and customers' opinions). This paper presents a framework for a Hospitality Big Data Warehouse (HBDW). The framework includes a (1) Web crawler that periodically accesses targeted websites to automatically extract information from them, and a (2) data model to organize and consolidate the collected data into a HBDW. Additionally, the usefulness of this HBDW to the development of the business analytical tools is discussed, keeping in mind the implementation of the business intelligence (BI) concepts.
- GyGSLA: A portable glove system for learning sign language alphabetPublication . Sousa, Luis; Rodrigues, João; Monteiro, Jânio; Cardoso, Pedro J. S.; Lam, RobertoThe communication between people with normal hearing with those having hearing or speech impairment is difficult. Learning a new alphabet is not always easy, especially when it is a sign language alphabet, which requires both hand skills and practice. This paper presents the GyGSLA system, standing as a completely portable setup created to help inexperienced people in the process of learning a new sign language alphabet. To achieve it, a computer/mobile game-interface and an hardware device, a wearable glove, were developed. When interacting with the computer or mobile device, using the wearable glove, the user is asked to represent alphabet letters and digits, by replicating the hand and fingers positions shown in a screen. The glove then sends the hand and fingers positions to the computer/mobile device using a wireless interface, which interprets the letter or digit that is being done by the user, and gives it a corresponding score. The system was tested with three completely inexperience sign language subjects, achieving a 76% average recognition ratio for the Portuguese sign language alphabet.
- Modular dynamic neural network: a continual learning architecturePublication . Turner, Daniel; Cardoso, Pedro; Rodrigues, JoãoLearning to recognize a new object after having learned to recognize other objects may be a simple task for a human, but not for machines. The present go-to approaches for teaching a machine to recognize a set of objects are based on the use of deep neural networks (DNN). So, intuitively, the solution for teaching new objects on the fly to a machine should be DNN. The problem is that the trained DNN weights used to classify the initial set of objects are extremely fragile, meaning that any change to those weights can severely damage the capacity to perform the initial recognitions; this phenomenon is known as catastrophic forgetting (CF). This paper presents a new (DNN) continual learning (CL) architecture that can deal with CF, the modular dynamic neural network (MDNN). The presented architecture consists of two main components: (a) the ResNet50-based feature extraction component as the backbone; and (b) the modular dynamic classification component, which consists of multiple sub-networks and progressively builds itself up in a tree-like structure that rearranges itself as it learns over time in such a way that each sub-network can function independently. The main contribution of the paper is a new architecture that is strongly based on its modular dynamic training feature. This modular structure allows for new classes to be added while only altering specific sub-networks in such a way that previously known classes are not forgotten. Tests on the CORe50 dataset showed results above the state of the art for CL architectures.