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		<title><![CDATA[ Computational Intelligence Magazine, IEEE - new TOC ]]></title>
		<link>http://ieeexplore.ieee.org</link>
		<description>TOC Alert for Publication# 10207 </description>
		<year>2012</year>
		<month>February </month>
		<day>10</day>
		<item>
			<title><![CDATA[[Front Cover]]]></title>
			<link><![CDATA[http://ieeexplore.ieee.org/xpls/abs_all.jsp?isnumber=6132197&arnumber=6132204]]></link>
			<description><![CDATA[ ]]></description>
			<pubDate><![CDATA[Feb.  2012]]></pubDate>
			<guid><![CDATA[http://ieeexplore.ieee.org/xpls/abs_all.jsp?isnumber=6132197&arnumber=6132204]]></guid>
			<volume>7</volume>
			<issue>1</issue>
			<startPage>C1</startPage>
			<endPage>C1</endPage>
			<fileSize>1704</fileSize>
			<authors><![CDATA[]]></authors>
		</item>
		<item>
			<title><![CDATA[[Table of Contents]]]></title>
			<link><![CDATA[http://ieeexplore.ieee.org/xpls/abs_all.jsp?isnumber=6132197&arnumber=6132210]]></link>
			<description><![CDATA[ ]]></description>
			<pubDate><![CDATA[Feb.  2012]]></pubDate>
			<guid><![CDATA[http://ieeexplore.ieee.org/xpls/abs_all.jsp?isnumber=6132197&arnumber=6132210]]></guid>
			<volume>7</volume>
			<issue>1</issue>
			<startPage>1</startPage>
			<endPage>1</endPage>
			<fileSize>337</fileSize>
			<authors><![CDATA[]]></authors>
		</item>
		<item>
			<title><![CDATA[CI at Work! [Editor's Remarks]]]></title>
			<link><![CDATA[http://ieeexplore.ieee.org/xpls/abs_all.jsp?isnumber=6132197&arnumber=6132221]]></link>
			<description><![CDATA[ ]]></description>
			<pubDate><![CDATA[Feb.  2012]]></pubDate>
			<guid><![CDATA[http://ieeexplore.ieee.org/xpls/abs_all.jsp?isnumber=6132197&arnumber=6132221]]></guid>
			<volume>7</volume>
			<issue>1</issue>
			<startPage>2</startPage>
			<endPage>18</endPage>
			<fileSize>441</fileSize>
			<authors><![CDATA[Tan, K. C.;]]></authors>
		</item>
		<item>
			<title><![CDATA[WCCI Is Going Down Under to Aussie, Mate! [President's Message]]]></title>
			<link><![CDATA[http://ieeexplore.ieee.org/xpls/abs_all.jsp?isnumber=6132197&arnumber=6132222]]></link>
			<description><![CDATA[ ]]></description>
			<pubDate><![CDATA[Feb.  2012]]></pubDate>
			<guid><![CDATA[http://ieeexplore.ieee.org/xpls/abs_all.jsp?isnumber=6132197&arnumber=6132222]]></guid>
			<volume>7</volume>
			<issue>1</issue>
			<startPage>3</startPage>
			<endPage>3</endPage>
			<fileSize>155</fileSize>
			<authors><![CDATA[Polycarpou, M. M.;]]></authors>
		</item>
		<item>
			<title><![CDATA[IEEE CIS Social Media: Have You Joined Our Online Community? [Society Briefs]]]></title>
			<link><![CDATA[http://ieeexplore.ieee.org/xpls/abs_all.jsp?isnumber=6132197&arnumber=6132224]]></link>
			<description><![CDATA[ ]]></description>
			<pubDate><![CDATA[Feb.  2012]]></pubDate>
			<guid><![CDATA[http://ieeexplore.ieee.org/xpls/abs_all.jsp?isnumber=6132197&arnumber=6132224]]></guid>
			<volume>7</volume>
			<issue>1</issue>
			<startPage>4</startPage>
			<endPage>79</endPage>
			<fileSize>272</fileSize>
			<authors><![CDATA[Lam, A.Y.S.;Watts, M.J.;Wu, D.D.;Estevez, P.A.;]]></authors>
		</item>
		<item>
			<title><![CDATA[CIS Publication Spotlight [Publication Spotlight]]]></title>
			<link><![CDATA[http://ieeexplore.ieee.org/xpls/abs_all.jsp?isnumber=6132197&arnumber=6132223]]></link>
			<description><![CDATA[ ]]></description>
			<pubDate><![CDATA[Feb.  2012]]></pubDate>
			<guid><![CDATA[http://ieeexplore.ieee.org/xpls/abs_all.jsp?isnumber=6132197&arnumber=6132223]]></guid>
			<volume>7</volume>
			<issue>1</issue>
			<startPage>6</startPage>
			<endPage>7</endPage>
			<fileSize>97</fileSize>
			<authors><![CDATA[Liu, D.D.;Lin, C-T.;Greenwood, G.G.;Lucas, S.S.;Zhengyou Z. Zhang;]]></authors>
		</item>
		<item>
			<title><![CDATA[Interview with the President of the IEEE Computational Intelligence Society, Marios M. Polycarpou [Career Profile]]]></title>
			<link><![CDATA[http://ieeexplore.ieee.org/xpls/abs_all.jsp?isnumber=6132197&arnumber=6132202]]></link>
			<description><![CDATA[ ]]></description>
			<pubDate><![CDATA[Feb.  2012]]></pubDate>
			<guid><![CDATA[http://ieeexplore.ieee.org/xpls/abs_all.jsp?isnumber=6132197&arnumber=6132202]]></guid>
			<volume>7</volume>
			<issue>1</issue>
			<startPage>8</startPage>
			<endPage>11</endPage>
			<fileSize>812</fileSize>
			<authors><![CDATA[]]></authors>
		</item>
		<item>
			<title><![CDATA[2011 IEEE Congress on Evolutionary Computation [Conference Reports]]]></title>
			<link><![CDATA[http://ieeexplore.ieee.org/xpls/abs_all.jsp?isnumber=6132197&arnumber=6132220]]></link>
			<description><![CDATA[ ]]></description>
			<pubDate><![CDATA[Feb.  2012]]></pubDate>
			<guid><![CDATA[http://ieeexplore.ieee.org/xpls/abs_all.jsp?isnumber=6132197&arnumber=6132220]]></guid>
			<volume>7</volume>
			<issue>1</issue>
			<startPage>12</startPage>
			<endPage>13</endPage>
			<fileSize>785</fileSize>
			<authors><![CDATA[Smith, A.A.;]]></authors>
		</item>
		<item>
			<title><![CDATA[2011 International Joint Conference on Neural Networks (IJCNN 2011) [Conference Reports]]]></title>
			<link><![CDATA[http://ieeexplore.ieee.org/xpls/abs_all.jsp?isnumber=6132197&arnumber=6132218]]></link>
			<description><![CDATA[ ]]></description>
			<pubDate><![CDATA[Feb.  2012]]></pubDate>
			<guid><![CDATA[http://ieeexplore.ieee.org/xpls/abs_all.jsp?isnumber=6132197&arnumber=6132218]]></guid>
			<volume>7</volume>
			<issue>1</issue>
			<startPage>13</startPage>
			<endPage>15</endPage>
			<fileSize>1063</fileSize>
			<authors><![CDATA[Minai, A.A.A.A.;]]></authors>
		</item>
		<item>
			<title><![CDATA[2011 IEEE Conference on Computational Intelligence and Games [Conference Reports]]]></title>
			<link><![CDATA[http://ieeexplore.ieee.org/xpls/abs_all.jsp?isnumber=6132197&arnumber=6132219]]></link>
			<description><![CDATA[ ]]></description>
			<pubDate><![CDATA[Feb.  2012]]></pubDate>
			<guid><![CDATA[http://ieeexplore.ieee.org/xpls/abs_all.jsp?isnumber=6132197&arnumber=6132219]]></guid>
			<volume>7</volume>
			<issue>1</issue>
			<startPage>15</startPage>
			<endPage>18</endPage>
			<fileSize>497</fileSize>
			<authors><![CDATA[Kim, K.-J.;Cho, S.-B.;]]></authors>
		</item>
		<item>
			<title><![CDATA[2012 IEEE World Congress on Computational Intelligence]]></title>
			<link><![CDATA[http://ieeexplore.ieee.org/xpls/abs_all.jsp?isnumber=6132197&arnumber=6132201]]></link>
			<description><![CDATA[ ]]></description>
			<pubDate><![CDATA[Feb.  2012]]></pubDate>
			<guid><![CDATA[http://ieeexplore.ieee.org/xpls/abs_all.jsp?isnumber=6132197&arnumber=6132201]]></guid>
			<volume>7</volume>
			<issue>1</issue>
			<startPage>19</startPage>
			<endPage>19</endPage>
			<fileSize>139</fileSize>
			<authors><![CDATA[]]></authors>
		</item>
		<item>
			<title><![CDATA[A Unified Framework for Symbiosis of Evolutionary Mechanisms with Application to Water Clusters Potential Model Design]]></title>
			<link><![CDATA[http://ieeexplore.ieee.org/xpls/abs_all.jsp?isnumber=6132197&arnumber=6132209]]></link>
			<description><![CDATA[This article presents a theoretic model for facilitating the emergence of productive search profiles transpiring from the symbiosis of gene (stochastic variation) and meme (lifetime learning) working in synergy. The evolvability measure of the symbiotic search profiles for each individual is quantified by means of statistical learning on distinct sample vectors encountered along the search. The most productive search profile inferred for an individual, as defined by evolvability measure, is subsequently used to work on it, leading to the self-configuration of solvers that acclimatizes to suit the given problem of interest. Empirical studies on representative problems are presented to reflect the characteristics of symbiotic evolution. Assessment made against several recent state-of-the-art evolutionary and adaptive search algorithms highlighted the efficacy of the theoretic formalism of evolutionary mechanisms in symbiosis for autonomic search. As the design of computationally cheap advanced empirical water models for the understanding of enigmatic properties of water remains an important and unsolved problem, the article presents an illustration of symbiotic evolution for the design of (H<sub>2</sub>O)<sub>n</sub> or water clusters potential model.]]></description>
			<pubDate><![CDATA[Feb.  2012]]></pubDate>
			<guid><![CDATA[http://ieeexplore.ieee.org/xpls/abs_all.jsp?isnumber=6132197&arnumber=6132209]]></guid>
			<volume>7</volume>
			<issue>1</issue>
			<startPage>20</startPage>
			<endPage>35</endPage>
			<fileSize>1833</fileSize>
			<authors><![CDATA[Minh Nghia Le;Yew Soon Ong;Yaochu Jin;Sendhoff, B.;]]></authors>
		</item>
		<item>
			<title><![CDATA[Multiobjective Synthesis of Six-Bar Mechanisms Under Manufacturing and Collision-Free Constraints]]></title>
			<link><![CDATA[http://ieeexplore.ieee.org/xpls/abs_all.jsp?isnumber=6132197&arnumber=6132203]]></link>
			<description><![CDATA[The purpose of this paper is to develop a new approach to evolutionary synthesis for applications involved in the design of collision-free linkage mechanisms. We first analyze the kinematical position, velocity, and acceleration equations for mechanisms in question and utilize the inferred equations to formulate practical collision- free requirements into geometrical constraints and convert manufacturing criteria into multiple objectives. In order to explore precise and widespread design solutions, we develop an improved version of the method of inequality-based multiobjective genetic algorithms (MMGA) by employing a Euclidean-distance-based diversity method, to serve as a global explorer. Several case studies are used to verify the correctness and effectiveness of the proposed approach, and the results have been successfully applied to the design of a commercial-use ladle mechanism, which has been hindered by obstacles from related peripheral equipment.]]></description>
			<pubDate><![CDATA[Feb.  2012]]></pubDate>
			<guid><![CDATA[http://ieeexplore.ieee.org/xpls/abs_all.jsp?isnumber=6132197&arnumber=6132203]]></guid>
			<volume>7</volume>
			<issue>1</issue>
			<startPage>36</startPage>
			<endPage>48</endPage>
			<fileSize>2042</fileSize>
			<authors><![CDATA[Chiu-Hung Chen;Tung-Kuan Liu;I-Ming Huang;Jyh-Horng Chou;]]></authors>
		</item>
		<item>
			<title><![CDATA[The Degree of Consideration-Based Mechanism of Thought and Its Application to Artificial Creatures for Behavior Selection]]></title>
			<link><![CDATA[http://ieeexplore.ieee.org/xpls/abs_all.jsp?isnumber=6132197&arnumber=6132208]]></link>
			<description><![CDATA[To make artificial creatures deliberately interact with their environment like living creatures, a behavior selection method mimicking living creatures thought mechanism is needed. For this purpose, there has been research based on probabilistic knowledge links between input (assumed fact) and target (behavior) symbols for reasoning. However, real intelligent creatures including human beings select a behavior based on the multi-criteria decision making process using the degree of consideration (DoC) for input symbols, i.e. will and context symbols, in their memory. In this paper, the DoC-based mechanism of thought (DoC-MoT) is proposed and applied to the behavior selection of artificial creatures. The knowledge links between input and behavior symbols are represented by the partial evaluation values of behaviors over each input symbol, and the degrees of consideration for input symbols are represented by the fuzzy measures. The proposed method selects a behavior through global evaluation by the fuzzy integral, as a multicriteria decision making process, of knowledge link strengths with respect to the fuzzy measure values. The effectiveness of the proposed behavior selection method is demonstrated by experiments carried out with a synthetic character Rity in the 3D virtual environment. The results show that the artificial creatures with various characteristics can be successfully created by the proposed DoC-MoT. Moreover, training the created artificial creatures to modify their characteristics was more efficient in the DoC-MoT than the probability-based mechanism of thought (P-MoT), both in terms of the number of parameters to be set and the amount of time consumed.]]></description>
			<pubDate><![CDATA[Feb.  2012]]></pubDate>
			<guid><![CDATA[http://ieeexplore.ieee.org/xpls/abs_all.jsp?isnumber=6132197&arnumber=6132208]]></guid>
			<volume>7</volume>
			<issue>1</issue>
			<startPage>49</startPage>
			<endPage>63</endPage>
			<fileSize>1456</fileSize>
			<authors><![CDATA[Jong-Hwan Kim;Woo-Ri Ko;Ji-Hyeong Han;Zaheer, S.A.;]]></authors>
		</item>
		<item>
			<title><![CDATA[Gesture Recognition Based on Localist Attractor Networks with Application to Robot Control [Application Notes]]]></title>
			<link><![CDATA[http://ieeexplore.ieee.org/xpls/abs_all.jsp?isnumber=6132197&arnumber=6132215]]></link>
			<description><![CDATA[In this work, we proposed an online gesture recognition method based on LAN. It was employed to recognize human gestures using streams of feature vectors extracted from real-time sensory data. As an application, the gesture recognition system was used to instruct the robot to execute the predefined commands such as moving in different directions, changing speed, stopping and so on. Experimental results showed a high accuracy in controlling the mobile robot using gesture recognition. This system provides a flexible and easy-to-use human-robot interface to control a robot. The user only needs to demonstrate all gesture patterns a few times before starting the control tasks. The robot is able to memorize all patterns and recognize a given gesture. Furthermore, in order to define a new pattern corresponding to a new control task, users only need to demonstrate this pattern. It is advantageous in the areas of service robots since many of them will be operated by non-expert users.]]></description>
			<pubDate><![CDATA[Feb.  2012]]></pubDate>
			<guid><![CDATA[http://ieeexplore.ieee.org/xpls/abs_all.jsp?isnumber=6132197&arnumber=6132215]]></guid>
			<volume>7</volume>
			<issue>1</issue>
			<startPage>64</startPage>
			<endPage>74</endPage>
			<fileSize>1666</fileSize>
			<authors><![CDATA[Rui Yan;Keng Peng Tee;Yuanwei Chua;Haizhou Li;Huajin Tang;]]></authors>
		</item>
		<item>
			<title><![CDATA[IEEE Transactions on Fuzzy Systems Special Issue on Advances in Type-2 Fuzzy Sets and Systems]]></title>
			<link><![CDATA[http://ieeexplore.ieee.org/xpls/abs_all.jsp?isnumber=6132197&arnumber=6132199]]></link>
			<description><![CDATA[ ]]></description>
			<pubDate><![CDATA[Feb.  2012]]></pubDate>
			<guid><![CDATA[http://ieeexplore.ieee.org/xpls/abs_all.jsp?isnumber=6132197&arnumber=6132199]]></guid>
			<volume>7</volume>
			<issue>1</issue>
			<startPage>75</startPage>
			<endPage>75</endPage>
			<fileSize>40</fileSize>
			<authors><![CDATA[]]></authors>
		</item>
		<item>
			<title><![CDATA[Fuzzy Networks for Complex Systems: A Modular Rule Base Approach (Gegov, A.; 2010) [Book Review]]]></title>
			<link><![CDATA[http://ieeexplore.ieee.org/xpls/abs_all.jsp?isnumber=6132197&arnumber=6132216]]></link>
			<description><![CDATA[The book ??Fuzzy Networks for Complex Systems?? by Alexander Gegov appears in the Springer Studies in Fuzziness and Soft Computing Series. Fuzzy networks as described here are networks where the nodes are fuzzy rule bases and there are connections between the nodes, for example inputting the outputs from one fuzzy system to another. In this book we get a complete description of the approach including the formal underpinning, practical examples, case studies and Matlab code to implement aspects of fuzzy networks.]]></description>
			<pubDate><![CDATA[Feb.  2012]]></pubDate>
			<guid><![CDATA[http://ieeexplore.ieee.org/xpls/abs_all.jsp?isnumber=6132197&arnumber=6132216]]></guid>
			<volume>7</volume>
			<issue>1</issue>
			<startPage>76</startPage>
			<endPage>77</endPage>
			<fileSize>576</fileSize>
			<authors><![CDATA[John, R.R.;]]></authors>
		</item>
		<item>
			<title><![CDATA[[Conference Calendar]]]></title>
			<link><![CDATA[http://ieeexplore.ieee.org/xpls/abs_all.jsp?isnumber=6132197&arnumber=6132217]]></link>
			<description><![CDATA[ ]]></description>
			<pubDate><![CDATA[Feb.  2012]]></pubDate>
			<guid><![CDATA[http://ieeexplore.ieee.org/xpls/abs_all.jsp?isnumber=6132197&arnumber=6132217]]></guid>
			<volume>7</volume>
			<issue>1</issue>
			<startPage>78</startPage>
			<endPage>79</endPage>
			<fileSize>276</fileSize>
			<authors><![CDATA[Fogel, G.G.;]]></authors>
		</item>
		<item>
			<title><![CDATA[IEEE Transactions on Neural Networks and Learning Systems]]></title>
			<link><![CDATA[http://ieeexplore.ieee.org/xpls/abs_all.jsp?isnumber=6132197&arnumber=6132200]]></link>
			<description><![CDATA[ ]]></description>
			<pubDate><![CDATA[Feb.  2012]]></pubDate>
			<guid><![CDATA[http://ieeexplore.ieee.org/xpls/abs_all.jsp?isnumber=6132197&arnumber=6132200]]></guid>
			<volume>7</volume>
			<issue>1</issue>
			<startPage>C3</startPage>
			<endPage>C3</endPage>
			<fileSize>28</fileSize>
			<authors><![CDATA[]]></authors>
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