Data mining techniques and information personalization have made significant growth in the past decade. Enormous volume of data is generated every day. Recommender systems can help users to find their specific information in the extensive volume of information. Several techniques have been presented for development of Recommender System (RS). One of these techniques is the Evolutionary Computin...

ePADD is free and open-source computational analysis software facilitating screening, browsing, and access for historically and culturally significant email collections. The software incorporates techniques from computer science and computational linguistics, including natural language processing, named entity recognition, and other statistical machine learningassociated processes. This demonst...

Although resilience is already an established field in system science and many methodologies and approaches are available to deal with it, the unprecedented scales of computing, of the massive data to be managed, new network technologies, and drastically new forms of massive scale applications bring new challenges that need to be addressed. This paper reviews the challenges and approaches of re...

Until recently, all the security measures have addressed servers or networks while clients or network endpoints have missed the required security concerns relatively. Most of the mechanisms safeguarding endpoints (clients) are software based. Making endpoints survive in open and reasonably exposed environments-like internet-demand that client security should stand by a tried and true dependence...

This work proposes novel methodologies to improve the use of Light Detection And Ranging (LiDAR) for environmental purposes, especially for thematic mapping (LiDAR only or fused with other remote sensors) and the estimation of forest variables. The methodologies make use of well-known techniques from soft computing (machine learning and evolutionary computation) and their adaptation to develop ...

This thesis presents a parallel programming model based on the gradual introduction of implementation detail. It comprises a series of decision stages that each fix a different facet of the implementation. The initial stages of the model elide many of the parallelisation concerns, while later stages allow low-level control over the implementation details. This allows the programmer to make deci...

ions. Finally we discuss the implementation of the PDE problem domain concepts. 3.1. Program construction and reasoning In order to build programs we need algorithm and data constructors, confer the slogan Algorithms + Data Structures = Programs [59]. Most of the early programming languages were strictly following the von Neumann machine model, i.e., sequential imperative programming languages....

IVith tl7e emerging applications of multi-agent systems, there is aluays a need for simulation to i~ertfi the results before actual implementation. Multi-agent sintulafion provides a test bed for several soflcompziting algorithms like f i z zy logic, learning automata, evolutionary olgorithms, etc. In this paper we discuss the fusion of these saff-computing methodologies and existing tools for ...