This study brings an evidence-based review of user individual characteristics employed as
sources of adaptation in recent adaptive learning systems. Twenty-two user individual …

Memetic computation is a paradigm that uses the notion of meme (s) as units of information
encoded in computational representations for the purpose of problem-solving. It covers a …

To enhance the search performance of evolutionary algorithms, reusing knowledge
captured from past optimization experiences along the search process has been proposed …

Multi-agent system is a rapidly developing field of distributed artificial intelligence that has
gained significant importance because of its ability to solve complex real-world problems. It …

With the rapid development of high-throughput DNA sequencing technologies, the amount
of DNA sequence data is accumulating exponentially. The huge influx of data creates new …

Ant colony optimization (ACO) has been successfully applied for combinatorial optimization
problems, eg, the travelling salesman problem (TSP), under stationary environments. In this …

In the distribution network fault management, service restoration is a very important
component. When a fault occurs, it is necessary to restore power to these deenergized loads …

Collaborative tagging represents for the Web a potential way for organizing and sharing
information and for heightening the capabilities of existing search engines. However …

Learners' emotional states might change during the learning process, and unpredictable
variations of a person's emotions raise the demand for regular assessment of feelings during …

Nowadays most people can get enough energy to maintain one‐day activity, while few
people know whether they eat healthily or not. It is quite important to analyze nutritional facts …