Augmented reality is a complex interdisciplinary field utilizing IT technologies in diverse areas such as medicine, education, architecture, industry, tourism and others, augmenting the real-time, real-world view with additional superimposed information in chosen format(s). The aim of this paper is to present an overview of both research and application aspects of using augmented reality technologies in tourism domain. While most research, and especially applications, are dealing with and developing visual-based augmented reality systems, there is a relevant amount of research discussing the utilization of other human senses such as tactioception and audioception, both being discussed within this work. A comprehensive literature analysis within this paper resulted with the identification, compilation and categorization of the key factors having the most relevant impact on the success of utilization of augmented technology in tourism domain.
Abstract-Massively Multi-Player On-Line Role-Playing Games (MMORPG) give us the opportunity to study two important aspects of computing: (1) large-scale virtual social interaction of people (players) and (2) the design, development and coordination of large-scale distributed artificial intelligence (AI). A common denominator for both aspects are the methods used to study them: social interaction can be described and simulated using agent-based models (ABM) whilst distributed AI is commonly modeled in terms of multi-agent systems (MAS). The important question to ask in both perspectives is how do agents organize in order to perform their tasks and reach their objectives? In the following paper we will present and overview of agent-based approaches to modeling MMORPG's agents including human players, artificial players (bots) and nonplaying characters (NPCs). We will put a special accent on useful agent behaviors, coordination and consensus mechanisms as well as organization and social network structure of agent societies.
In the field of face biometrics, finding the identity of a person in an image is most researched, but there are other, soft biometric information that are equally as important, such as age, gender, ethnicity or emotion. Nowadays, ethnicity classification has a wide application area and is a prolific area of research. This paper gives an overview of recent advances in ethnicity classification with focus on convolutional neural networks (CNNs) and proposes a new ethnicity classification method using only the middle part of the face and CNN. The paper also compares the differences in results of CNN with and without plotted landmarks. The proposed model was tested using holdout testing method on UTKFace dataset and FairFace dataset. The accuracy of the model was 80.34% for classification into five classes and 61.74% for classification into seven classes, which is slightly better than state-of-the-art, but it is also important to note that results in this paper are obtained by using only the middle part of the face which reduces the time and resources necessary.
This paper explores the benefits of using Virtual Reality (VR) technologies in higher education. The theoretical part investigates the classical education system and its features in order to compare advantages of using VR systems in education. VR technologies and its current state in industry and in education were explored in addition to which branches of higher education use these systems. A survey was conducted through an online questionnaire where respondents (N = 55) gave their opinion on VR and the implementation of VR technologies in education. Three hypotheses related to the use of VR technology, student interest, and learning outcomes as well as the effectiveness, immersiveness and the effect of VR systems on the users were tested through 27 questions.
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