E-learning has become an important part of our educational life with the development of e-learning systems and platforms and the need for online and remote learning. ICT and computational intelligence techniques are being used to design more intelligent and adaptive systems. However, the art of designing good real-time e-learning systems is difficult as different aspects of learning need to be considered including challenges such as learning rates, involvement, knowledge, qualifications, as well as networking and security issues. The earlier concepts of standalone integrated virtual e-learning systems have been greatly enhanced with emerging technologies such as cloud computing, mobile computing, big data, Internet of Things (IoT), AI and machine learning, and AR/VT technologies. With this book, the editors and authors wish to help researchers, scholars, professionals, lecturers, instructors, developers, and designers understand the fundamental concepts, challenges, methodologies and technologies for the design of performant and reliable intelligent and adaptive real time e-learning systems and platforms. This edited volume covers state of the art topics including user modeling for e-learning systems and cloud, IOT, and mobile-based frameworks. It also considers security challenges and ethical conduct using Blockchain technology.

To improve the robustness and discrimination power of the triangle-area representation, a novel shape matching method based on multi-scale angle representation is proposed in this study. By analysing the configurations of different sample points from each shape contour, shape descriptors are constructed by using space angles at different scale levels. With the proposed shape representation, the multi-scale information of shape contours is efficiently described, and the dynamic programming is further used to determine the correspondence between samples from different shapes and calculate the shape distance in the feature matching step. Moreover, to improve the shape retrieval results based on pairwise shape distances, the dynamic label propagation is introduced as the post-processing step. Unlike previous distance learning methods learning the database manifold implicitly, the authors method retrieves relative objects on the shortest paths from near to far explicitly, and the underlying structure can be effectively captured. The proposed method tested on different shape databases provides the performances superior to many other methods, and it can be applied to visual data processing and understanding of the internet of things.

As the world continuously faces humanitarian disasters, there is an ever-increasing need to find ICT-based solutions to overcome complex problems. In other words, though ICTs have changed the lives of people at the operative level, many ICTs' contributions are yet to be uncovered in humanitarian service. Therefore, this book provides new developments, innovations, and research outcomes; case studies and lessons learnt; and other considerations for the creation and deployment of effective ICTs to provide humanitarian services for the resource-constrained and vulnerable populations in the world in order to improve their lives.

Humanitarian services seek to promote welfare to save lives, maintain human dignity, alleviate suffering, strengthen preparedness, and provide material and logistical assistance in response to humanitarian crises. They are thus different from development aids that address underlying socioeconomic factors and provides support for the social, economic and political developments of developing nations. Information and Communication Technologies (ICTs) are becoming the backbone technologies for providing quality and efficient services and are playing an increasingly important and sophisticated role in humanitarian-service activities. Many ICT-based solutions exist such as tools to support the work of humanitarian organizations, mobile applications and solutions to provide health services, open source web portals for disaster management systems, and mobile and autonomous devices to provide assistance. This edited book covers new developments, innovations, and research outcomes for the creation and deployment of effective ICT technologies and solutions to support humanitarian services. Coverage includes theories as well as information, mobile and networking applications that foster information exchange and cooperation in the humanitarian and emergency management fields. Aimed at ICT and computer engineers, professionals, and researchers working on practical and lasting ICT solutions to support humanitarian services, this will also be a useful reference for advanced students and lecturers in the field, entrepreneurs and researchers from government, non-government and industry organizations, as well as professionals in NGO organizations, ethics committees, and policymakers.

Gamification refers to the use of rules and game design techniques to involve and motivate people to achieve their goals. This work proposes an application development architecture that can generate game applications with gamification techniques. As proof of concept, the authors introduce Zeus, a platform for developing ruled-based serious game applications with gamification techniques. Zeus aims at generating gamified applications that can meet the learning goals set by users. These goals will be reflected through both learning and game attributes that users can personally select. To assess the functionality of the authors tool, they conduct a qualitative evaluation of four rule-based serious game applications developed with Zeus to help students learn about arithmetic. They make use of the Fun Toolkit to perform this evaluation in terms of the delivery of both fun and learning experiences. Their findings are encouraging in the context of learning basic arithmetic operations with Zeus game applications.

The Defence Wargaming Centre (DWC), located on Dstl's Portsdown West site near Portsmouth, was created to host wargames for all three UK services, responding to the increasing demand for wargaming as a tool both to support decisions and to develop insight into complex issues faced by defence and security. By delivering a wide variety of wargames it represents a significant step-up in capability and signals our intent to keep developing in response to growing MoD and wider government demand for wargaming.

Adaptive metacognitive scaffolding is developed to provide learning assistance on an as-needed basis; thus, advances the effectiveness of computer-based learning systems. Metacognitive scaffoldings have been developed for some science subjects; however, not for algorithm-learning. The learning algorithm is different from learning science as it is more oriented to problem-solving; therefore, this study is aimed to describe the modelling, development, and evaluation of the adaptive metacognitive scaffolding which is dedicated for encouraging algorithm-learning. In addition, the authors present a new approach for learner modelling to find students’ metacognitive state. Adaptivity of the scaffolding is based on the learner modelling. To evaluate the effectiveness of the developed system, it is deployed in a real algorithm-learning classroom of 38 students. The class is randomly divided into two groups: experiment and control. Two parameters are measured from both groups, i.e. academic success and academic satisfaction. Non-parametric statistical test, i.e. Mann–Whitney U-test (significance level 0.01) rejects the null hypothesis (U-value = 86.5 and U-critical = 101). This result verifies that the academic success of the experiment group is significantly higher than that of the control group. In addition, an academic satisfaction survey shows that adaptive scaffolding is valid in assisting students while learning with the system.

Synthetic biology is a relatively young field, although it builds upon disciplines whose roots go back centuries. Recently, its practitioners have tended to move into the field out of interest or by chance, and come from a wide variety of backgrounds. It is also a very fast-moving field; new protocols, laboratory equipment, computational facilities and algorithms are being developed at a rapid pace. Students who start studying synthetic biology at an undergraduate or postgraduate level will, in the course of their careers, work with technologies as yet undreamt of, and will do so mostly in the context of highly interdisciplinary teams. In this study, the authors identify some of the key areas required for the education of new synthetic biologists to equip them with both adequate background and sufficient flexibility to tackle these challenges and therefore to future-proof synthetic biology.

Numerical cognition is a distinctive component of human intelligence such that the observation of its practice provides a window in high-level brain function. The modelling of numerical abilities in artificial cognitive systems can help to confirm existing child development hypotheses and define new ones by means of computational simulations. Meanwhile, new research will help to discover innovative principles for the design of artificial agents with advanced reasoning capabilities and clarify the underlying algorithms (e.g. deep learning) that can be highly effective but difficult to understand for humans. This study promotes new investigation by providing a common resource for researchers with different backgrounds, including computer science, robotics, neuroscience, psychology, and education, who are interested in pursuing scientific collaboration on mutually stimulating research on this topic. The study emphasises the fundamental role of embodiment in the initial development of numerical cognition in children. This strong relationship with the body motivates the cognitive developmental robotics (CDR) approach for new research that can (among others) help standardise data collection and provide open databases for benchmarking computational models. Furthermore, the authors discuss the potential application of robots in classrooms and argue that the CDR approach can be extended to assist educators and favour mathematical education.

With the rapid development of network information technology and the wide application of smart phones, tablet PCs and other mobile terminals, online education plays an increasingly important role in social life. This article focuses on mining useful data from the massive online education data, by using transfer learning, relying on Hadoop, to construct Online education data classification framework (OEDCF), and design an algorithm Tr_MAdaBoost. This algorithm overcomes the traditional classification algorithms in which the required data must be restricted to independent and identically distributed data, since online education using this new algorithm can achieve the correct classification even it has different data distribution. At the same time, with the help of Hadoop's parallel processing architecture, OEDCF can greatly enhance the efficiency of data processing, create favorable conditions for learning analysis, and promote personalized learning and other activities of big data era.