Embedding Computational Intelligence in Pervasive Spaces

This paper presents how to embed AI mechanisms in pervasive spaces to produce more intelligent, adaptive, and convenient environments. The paper also concentrated on computational intelligence in particular, fuzzy systems and neural networks because this emerging AI domain covers most of the requirements for this task.     

Online Learning and Adaptation of Autonomous Mobile Robots for Sustainable Agriculture

In this paper we will introduce the application of our newly patented double hierarchical Fuzzy-Genetic system (British patent 99-10539.7) to produce an intelligent autonomous outdoor agricultural mobile robot capable of learning and calibrating its controller online in a short time interval and implementing a life long learning strategy. The online and life long learning strategy allow the outdoor robots to increase their experience and adapt their controllers in the face of the changing and dynamic unstructured outdoor agricultural environments. Such characteristics permit prolonged periods of operation within dynamic agricultural environments, which is an essential feature for the realization of a platform vehicle for use in sustainable agriculture and organic farming.     

Lower-bound time-complexity greening mechanism for duplication-based scheduling on large-scale computing platforms

The Journal of Supercomputing - Large-scale computing platforms become essential in nowadays business and scientific activities. The electrical energy consumed by such platforms increases...     

What Computing with Words Means to Me [Discussion Forum]

Computing with words (CWW) means different things to different people. This article is the start of a position paper, written by some of the members of the CIS Fuzzy Systems Technical Committee Task Force on CWW, that answers the question "What does CWW mean to me?"     

Inhabited Intelligent Environments

There is an increasing amount of research into the area of pervasive computing, smart homes and intelligent spaces, one example being that of the DTI-funded Pervasive Home Environment Networking (PHEN) project. Much of the current research focuses on environments populated by numerous computing devices, sensors, actuators, various wired and wireless networking systems and poses the question of how such computing environments might become ‘intelligent’? Often, the proposed solution is to explicitly preprogram in the intelligence. In this paper we discuss a solution based on embedded-agents which enables emergent intelligent behaviour by predominantly implicit processes. We describe an experimental test-bed for pervasive computing, the iDorm, and report on experiments that scope the agent-learning characteristics in such environments. We also introduce a more human-directed approach to programming in pervasive environments which we refer to as task-oriented programming (TOP).     

Comments on "Dynamical optimal training for interval type-2 fuzzy neural network (T2FNN)".

In this comment, it will be shown that the backpropagation (BP) equations by Wang et al. are not correct. These BP equations were used to tune the parameters of the antecedent type-2 membership functions as well as the consequent part of the interval type-2 fuzzy neural networks (T2FNNs). These incorrect equations would have led to erroneous results, and hence this might affect the comparisons and findings presented by Wang et al. This comment will highlight the correct BP tuning equations for the T2FNN.     

Low power and high-speed FPGA implementation for 4D memristor chaotic system for image encryption

In this paper, we proposed a novel low power and high-speed FPGA implementation of the 4D memristor chaotic system with cubic nonlinearity based on Xilinx System Generator (XSG) model. Firstly, a pseudo-random number generator based on the proposed XSG FPGA implementation of the proposed 4D memristor chaotic system which implemented into Xilinx Spartan-6 X6SLX45 board with 32 fixed-point format. The aim of the FPGA implementation is increasing the frequency of the memristor chaotic random number generators. The FPGA implementation of the memristor chaotic system results show that the new design approach achieves a maximum frequency of 393 MHz and dissipates 117 m watt. The standard fifteen randomization tests are used to measure the quality of the proposed pseudo-random number generator based on the 4D memristor chaotic system and it gives an excellent randomization analysis. Also, the gray image encryption scheme based on the 4D memristor chaotic system has been introduced. The proposed cryptosystem has a large keyspace, very low correlation values, high entropy which is much closer to the ideal entropy value, a high number of pixels change rate and high unified average changing intensity values. The results and security analysis of the proposed encryption scheme demonstrate that the investigated encryption approach can protect high speed and high security against various attack.

     

A type 2-hesitation fuzzy logic based multi-criteria group decision making system for intelligent shared environments

Intelligent environments aim to maximize the user comfort and safety while achieving other objectives such as energy minimization. Intelligent shared spaces (such as homes, classrooms, offices, libraries, etc.) need to consider the preferences of users from diverse backgrounds. However, there are high levels of uncertainties faced in intelligent shared spaces. Hence, there is a need to employ intelligent decision making systems which can consider the various users preferences and criteria in order to achieve the convenience of the various users while handling the faced uncertainties. Therefore, we propose a Fuzzy Logic-Multi-Criteria Group Decision Making (FL-MCGDM) system which provides a comprehensive valuation from a group of users/decision makers based on the aggregation of users’ opinions and preferences. The proposed FL-MCGDM system employs an interval type-2 fuzzy logic and hesitation index [from Intuitionistic Fuzzy Sets (IFSs)]. We have carried out experiments in the intelligent apartment (iSpace) located in the University of Essex to evaluate various approaches employing group decision making techniques for illumination selection in an intelligent shared environment. It was found that the Footprint of Uncertainty (of interval type-2 fuzzy sets) and hesitation index (of intuitionistic fuzzy sets (IFSs)) are able to provide a measure of the uncertainties present among the various decision makers. The proposed Type 2-Hesitation FL-MCGDM system better agrees with the users’ decision compared to existing fuzzy MCDM including the Fuzzy Logic based TOPSIS (Technique for Order of Preference by Similarity to Ideal Solution), type-1 FL-MCGDM and interval type-2 in FL-MCGDM.