Digital information has redefined the way in which both public and private organizations are faced with the use of data to improve decision making. The importance of Big Data lies in the huge amount of data generated every day, especially following the emergence of online social networks (Facebook, Twitter, Google Plus, etc.) and the exponential growth of devices such as smartphones, smartwatches and other wearables, sensor networks, etc. as well as the possibility of taking into account increasingly updated and more varied information for decision making.

With proper Big Data analysis we can spot trends, get models from historical data for predicting future events or extract patterns from user behaviour, and thus be able to tailor services to the needs of users in a better way.

Using Big Data is becoming widespread among organizations of all kinds. It is a fact that large companies, start-ups, government agencies and non-governmental organizations are gradually being encouraged to use microdata generated by digital devices to operate more efficiently. When these microdata are aggregated they turn into massive amounts of data which require specialized tools and skills to be managed.

The challenge organizations are facing is that the increasing amount of data is too large or too unstructured to be managed and analysed with traditional methods. Think of the data derived from the sequence of clicks from the Web, social media content - tweets, blogs, Facebook wall postings (Facebook alone accounts for more than 1 billion active users generating social interaction content. Google processes on average over 53 thousand search queries per second, making it over 4.6 billion in a single day) - or radio frequency identification systems, which generate up to a thousand times more data than conventional barcode systems (12 million RFID tags – used to capture data and track movement of objects in physical world – had been sold in by 2011. By 2021, it is estimated that that number will have risen to 209 billion. Walmart manages more than 1 million customer transactions per hour). In the World 10.000 payment card transactions are recorded every second. The amount of data transferred over mobile networks increased by 81% to 1.5 Exabyte per month between 2012 and 2014. More than 5 billion people make phone calls, send text messages and surf the Internet with mobile phones. Every day they send 340 million tweets (4.000 per second!). To date they’ve generated 2.5 trillion bytes of data. However, very little of this information is in the form of rows and columns of traditional databases.

The research works presented in this issue are based on various topics of interest, among which are included: 3D Interface, Information Extraction, Artificial immune system, Security  in Cloud Computing, Genetic Algorithm, Activity recognition, 3D Render Distribution, Software visualization, Event Perception, New Programming Language, Distributed computing, MOOC environments, etc.

The International Journal of Interactive Multimedia and Artificial Intelligence provides an interdisciplinary forum in which scientists and professionals can share their research results and report new advances on Artificial Intelligence and Interactive Multimedia techniques.

The term 'Digital Economy' was coined for the first time by Don Tapscott in 1995 in his best-seller The Digital Economy: Promise and Peril in the Age of Networked Intelligence. When he wrote the book 20 years ago, he announced how he thought the Internet would fully transform the nature of business and government. We have now extended the concept, illustrating how digital technologies are rapidly transforming business practices, the economy and societies. Technology, and its impact on business strategy and society, continues to rise in importance. The Digital Economy, sometimes also called “Digital Business” has become a philosophy for many top executive teams as they seek competitive advantages in a world of fast moving technological change. When we talk about digital technologies, we are not only talking about the internet, nor only ICT (Information and Communications Technology), but other concepts such as mobile, telecommunications or content. The digital economy is by no means an exclusively economic concept. Therefore, it might be more appropriate to speak of digital society or digital technology. What matters is that digital is a transverse concept that affects individuals, businesses and public administrations.

People are progressively entering the digital world. In our daily life we are in direct contact with digital devices such as cars, electrical appliances etc. People increasingly communicate digitally; through mobile devices, internet, and social networks. In addition, our leisure, education and health are largely being integrated into a digital environment.

Likewise, organizations are progressively incorporating digital technology in their production and distribution processes, conducting research and also in the process of decision making. In this sense the emergence of Big Data has been one factor that has accelerated an already observed trend.

Public administrations and political institutions are incorporating digital into both their internal procedures and in their relationships with citizens. An example is the role played by Big Data in the two elections won by Obama. Another example may be the way the ISIS terrorist group uses social networking to publicize their activities and secure funding.

But digital technology and information are not only affecting the daily behavior of individuals, businesses and public administrations. They are also playing a very prominent role in the knowledge of the fundamental laws of nature. In this sense we can highlight the contribution of digital technology in the computer modeling of fundamental elements of life, and consequently in the creation of artificial life. Likewise, you may also note the role in deepening the knowledge of the universe.

Bearing in mind that Digital Economy is becoming more relevant from the economic perspective, we decided to star this issue with something unusual in this magazine: a paper that discusses the economy. It’s interesting from our point of view, as it underscores the fact that digital technologies, which of course include Artificial Intelligence and Interactive Multimedia, are not only relevant from the technical point of view, but from the business and society perspective as well.

The research works presented in this issue are based on various topics of interest, among which are included:  bayesian networks, evolutionary algorithms, virtual reality, web advertising, 3D technologies, traffic expression, Smart Cities, computational sustainability, computer vision, image recognition, deep neural networks, graphical models, mobile devices, human/complex system interactions, multi-agent systems, physics inspired behaviours, etc.

The International Journal of Interactive Multimedia and Artificial Intelligence provides an interdisciplinary forum in which scientists and professionals can share their research results and report new advances on Artificial Intelligence and Interactive Multimedia techniques.

This special issue, Special Issue on Multisensor user tracking and analytics to improve education and other application fields, concentrates on the practical and experimental use of data mining and analytics techniques, specially focusing on the educational area. The selected papers deal with the most relevant issues in the field, such as the integration of data from different sources, the identification of data suitable for the problem analysis, and the validation of the analytics techniques as support in the decision making process. The application fields of the analytics techniques presented in this paper have a clear focus on the educational area (where Learning Analytics has emerged as a buzzword in the recent years) but not restricted to it. The result is a collection of use cases, experimental validations and analytics systems with a clear contribution to the state of the art.

The International Journal of Interactive Multimedia and Artificial Intelligence provides an interdisciplinary forum in which scientists and professionals can share their research results and report new advances on Artificial Intelligence and Interactive Multimedia techniques.

The research works presented in this issue are based on various topics of interest, among which are included:  3D image reconstruction, Persian texts, usability evaluation methods, user experience, oriented matroids, flexible job-shop scheduling, business and social behavior, mobile computing and mobile devices, intelligent tutoring systems and geography optimization.

Pacheco et al. present a novel hybrid methodology, composed by 10 phases that combine active and passive methods, using images and a laser in order to supplement the missing information and obtain better results in the 3D object reconstruction. The proposed methodology proved its efficiency in two complex topological complex objects.

Noferesti, S. and Shamsfard M., write about Persian Texts and the Ezafe construction. They introduce a framework for combining genetic algorithms with rule-based models. This framework was used for recognizing the position of Ezafe constructions in Persian written texts. At the first stage, the rule-based model was applied to tag some tokens of an input sentence. Then, in the second stage, the search capabilities of the genetic algorithm were used to assign the Ezafe tag to untagged tokens using the previously captured training information. The proposed framework was evaluated on Peykareh corpus and it achieved 95.26 percent accuracy. Test results show that this proposed approach outperformed other approaches for recognizing the position of Ezafe constructions.

Schön, E.M. et al. describe a procedure to analyze and optimize scientific Internet information services that can be accomplished with relatively low effort. It consists of a combination of methods that already have been successfully applied to practice: Human beings, usability inspections, Online Questionnaire, Kano model and Web Analytics [3].

José Antonio Valero Medina and Ivan Lizarazo Salcedo describe the implementation of a prototype REST service for triangulation of point sets collected by mobile GPS receivers. The first objective of their work is to test functionalities of an application, which exploits mobile devices’ capabilities to get data associated with their spatial location.  A triangulation of a set of points provides a mechanism through which it is possible to produce an accurate representation of spatial data. Such triangulation may be used for representing surfaces by Triangulated Irregular Networks (TINs), and for decomposing complex two-dimensional spatial objects into simpler geometries. The second objective is to promote the use of oriented matroids for finding alternative solutions to spatial data processing and analysis tasks. This study focused on the particular case of the calculation of triangulations based on oriented matroids. The prototype described used a wrapper to integrate and expose several tools previously implemented in C++.

Celia Gutiérrez proposes a work based on an algorithm where each objective (resource allocation, start-time assignment) is solved by a genetic algorithm (GA) that optimizes a particular fitness function, and enhances the results by the execution of a set of heuristics that evaluate and repair each scheduling constraint on each operation. The flexible Job-shop Scheduling Problem (fJSP) considers the execution of jobs by a set of candidate resources while satisfying time and technological constraints. The aim of this work is to analyze the impact of some algorithmic features of the overlap constraint heuristics, in order to achieve the objectives at a highest degree. To demonstrate the efficiency of this approach, experimentation has been performed and compared with similar cases, tuning the GA parameters correctly.

Zouhair et al. present a work in the field of Intelligent Tutoring System (ITS), in fact, there is still the problem of knowing how to ensure an individualized and continuous learners follow-up during learning process, indeed among the numerous methods proposed, very few systems concentrate on a real time learners follow-up. This research develops the design and implementation of a Multi-Agents System Based on Dynamic Case Based Reasoning which can initiate learning and provide an individualized follow-up of learner. This approach involves the use of Dynamic Case Based Reasoning to retrieve the past experiences that are similar to the learner’s traces (traces in progress), and the use of Multi-Agents System. Through monitoring, comparing and analyzing learner traces, the system keeps a constant intelligent watch on the platform, and therefore, it detects the difficulties hindering progress and  avoids possible dropping out. The system can support any learning subject. To help and guide the learner, the system is equipped with combined virtual and human tutor [6].

Sati, M. et al. outline a solution about a fault-tolerant mobile computing model based on scalable replica. The most frequent challenge faced by mobile user is stay connected with online data, while disconnected or poorly connected store the replica of critical data. Nomadic users require replication to store copies of critical data on their mobile machines. Existing replication services do not provide all classes of mobile users with the capabilities they require, which includes: the ability for direct synchronization between any two replicas, support for large numbers of replicas, and detailed control over what files reside on their local (mobile) replica. Existing peer-to-peer solutions would enable direct communication, but suffers from dramatic scaling problems in the number of replicas, limiting the number of overall users and impacting performance. Roam is a replication system designed to satisfy the requirements of the mobile user. Roam is based on the Ward Model, replication architecture for mobile environments. Using the Ward Model and new distributed algorithms, Roam provides a scalable replication solution for the mobile user. They describe the motivation, design, and implementation of Roam and report its performance. Replication is extremely important in mobile environments because nomadic users require local copies of important data.

Bhaskar, V.S. et al., describe the work to elaborate swarm intelligence for business intelligence decision making and the business rules management improvement. Their paper introduces the decision making model which is based on the application of Artificial Neural Networks (ANNs) and Particle Swarm Optimization (PSO) algorithm. Essentially the business spatial data illustrate the group behaviors. The swarm optimization, which is highly influenced by the behavior of creature, performs in group. The Spatial data is defined as data that is represented by 2D or 3D images. SQL Server supports only 2D images till now. As they know that location is an essential part of any organizational data as well as business data: enterprises maintain customer address lists, own property, ship goods from and to warehouses, manage transport flows among their workforce, and perform many other activities. By means to say a lot of spatial data is used and processed by enterprises, organizations and other bodies in order to make the things more visible and self-descriptive. From the experiments, they found that PSO is can facilitate the intelligence in social and business behaviour.

Dixit, P. et al. write about the Internet security. This topic deals with the information secure and the integrity of the data. Sending messages over the Internet secretly is one of the major tasks as it is widely used for passing the message. In order to achieve security there must be some mechanism to protect the data against unauthorized access. A lossless data hiding scheme is proposed in this paper which has a higher embedding capacity than other schemes. Unlike other schemes that are used for embedding fixed amount of data, the proposed data hiding method is block based approach and it uses a variable data embedding in different blocks which reduces the chances of distortion and increases the hiding capacity of the image. When the data is recovered the original image can be restored without any distortion. The experimental results indicate that the proposed solution can significantly support the data hiding problem. We achieved good Peak signal-to-noise ratio (PSNR) while hiding large amount of data into smoother regions.

The science of happiness is trans-disciplinary. Happiness is an experience human beings have and, in consequence, its understanding calls for knowledge from all disciplines which, in one way or the other, deal with all facets of human lives. Various disciplines have contributed to the development of the science of happiness; among them: Psychology, Sociology, Economics, Psychiatry and Neuroscience. Because happiness research deals with human being of flesh and blood, it requires high-level techniques to dealing with large information sets in order to extract that information which is relevant. In the study of happiness there are many observations –as many as persons in the world-, there are many variables, and there are many interrelations and synergies to take account of. In consequence, happiness research benefits from sophisticated models that allow for a better understanding of people’s happiness; without losing contact with what real human beings experience, it is important to use techniques that allow researchers to process all the information reaching for valuable conclusions. It is with this purpose that Computer Science has joined the other disciplines providing its calculation powerful tools to advance the study of happiness. It is therefore appropriate that The International Journal of Interactive Multimedia and Artificial Intelligence has decided to launch a special issue on happiness showing some of the potential contributions the discipline can make to happiness research.

The research works presented in this issue cover various topics of interest, all related to potential contributions from Computer Science to the understanding of happiness and subjective well-being. 

The research works presented in this issue are based on various topics of interest, among which are included:  Mobile services, mpeg, agent-based Simulation, complexity, management accounting systems, animal-drawn vehicles, traffic and transport, possibility theory, precautionary saving, MAS, ambient intelligence, gamification, sustainable environments, disaster recovery, DSS, constraint programming and ICT.

López et al. presents the progress and final state of CAIN-21, an extensible and metadata driven multimedia adaptation in the MPEG-21 framework. CAIN-21 facilitates the integration of pluggable multimedia adaptation tools. To drive the adaptation, it uses the description tools and implied ontology established by MPEG-21. The paper not only describes the evolution and latest version of CAIN-21, but also identifies limitations and ambiguities in the description capabilities of MPEG-21.

Friederike Wall investigates the effectiveness of reducing errors in management accounting systems with respect to organizational performance. In particular, different basic design options of management accounting systems of how to improve the information base by measurements of actual values are analyzed in different organizational contexts. The results provide broad, but no universal support for conventional wisdom that lower inaccuracies of accounting information lead to more effective adaptation processes. Furthermore, results indicate that the effectiveness of improving the management accounting system subtly interferes with the complexity of the interactions within the organization and the coordination mode applied.

Sánchez-Aparicio et al. analyzes the structure of the data collected in the population dependent or receives its revenues in the use of animal-drawn vehicle, to extract an economic model for the development of this activity introducing formal parameters, as well as replacement of the vehicle analyzes the development of this activity in this population.

Ana María Lucia Casademunt and Irina Georgescu study the optimal saving problem in the framework of possibility theory. The notion of possibilistic precautionary saving is introduced as a measure of the way the presence of possibilistic risk (represented by a fuzzy number) influences a consumer in establishing the level of optimal saving. The notion of prudence of an agent in the face of possibilistic risk is defined and the equivalence between the prudence condition and a positive possibilistic precautionary saving is proved. Some relations between possibilistic risk aversion, prudence and possibilistic precautionary saving were established.

Celia Gutiérrez proposes a framework that incorporates robust analysis tools using IDKAnalysis2.0 to evaluate bullying effect in communications. The work is based on ICARO-T. This platform follows the Adaptive Multi-agent Systems paradigm. Experimentation with ICARO-T includes two deployments: the equitative and the authoritative. Results confirm the usefulness of the analysis tools when exporting to Cooperative Multi-agent Systems that use different configurations. Besides, ICARO-T is provided with new functionality by a set of tools for communication analysis.

Silva et al. presents an approach which uses information from different environments, ranking them according to their sustainability assessment. Recommendations are then computed using similarity and clustering functions ranking users and environments, updating their previous records and launching new recommendations in the process. Gamification concepts are used in order to keep users motivation and engage them actively to produce better results in terms of sustainabilit.

Caianiello et al. outline a solution to the problem of intelligent control of energy consumption of a smart building system by a prosumer planning agent that acts on the base of the knowledge of the system state and of a prediction of future states. Predictions are obtained by using a synthetic model of the system as obtained with a machine learning approach. They present case studies simulations implementing different instantiations of agents that control an air conditioner according to temperature set points dynamically chosen by the user. The agents are able of energy saving while trying to keep indoor temperature within a given comfort interval.

Amadini et al., propose an approach that could be used as a decision support tool for a post-disaster response that allows the assignment of victims to hospitals and organizes their transportation via emergency vehicles. By exploiting the synergy between Mixed Integer Programming and Constraint Programming techniques, we are able to compute the routing of the vehicles so as to rescue much more victims than both heuristic based and complete approaches in a very reasonable time.

Juan Carlos Piedra Calderón and  J. Javier Rainer explain the big influence of Information and Communication Technologies (ICT), especially in area of construction of Technological Societies. There are many changes that are visible in the way of relating to people in different environments. These changes have the possibility to expand the frontiers of knowledge through sharing and cooperation. That has meaning the inherently creation of a new form of Collaborative Knowledge. The potential of this Collaborative Knowledge has been given through ICT in combination with Artificial Intelligence processes, from where is obtained a Collective Knowledge. When this kind of knowledge is shared, it gives the place to the Global Collective Intelligence.

Guedes et al., proposes the definition of a system to negotiate products in an e-commerce scenario. This negotiation system is defined as PLANE – Platform to Assist Negotiation – and it is carried in a semi-automatic way, using multi-attributes functions, based on attributes of the negotiated content. It also presents an architecture to interconnect the participant through an inter-network in the television broadcasters context. Results demonstrated the success of the system in approximate the negotiator after some few interactions, reducing time and cost.