Anyone who uses Maya, Unreal, and similar large software, whose development is fast pace, will find each version is different from it's previous one. Moreover, tutorials that come with the software, let alone hundreds available online, are often out of date and lack behind. As Maya concerned, here are few changes we found, in the labs I run, when using Maya 2008 from main tutorials often used.
Whenever 'Edit Polygons' menu are mentioned you can change that to 'Edit Mesh' menu. Similarly, whenever 'Split' is required you can use 'Detach Components' in the 'Edit Mesh' menu. As for 'Extrude' there is a menu entry for it under 'Edit Mesh'.
There are obviously more changes in menu names but those we have found so far. My advice to my students is always to look at what the tutorial tells them to do and not necessary at how the tutorial tells them to do it. This may be of help to those working with Maya and other fast paced software where tutorials do not necessary keep up with the changes in the software.
Wednesday 18 February 2009
Wednesday 4 February 2009
From Swarm Sensors to Emotional Modeling
I will be giving a talk at University of Lincoln on 5th Feb 2009 in which I will be combining two projects. They may seem to be unrelated. Here is the abstract with some related publications.
==============================
The talk will cover briefly two main research areas. The first part of the talk will look at current work undertaking to use swarm intelligence in optimizing sensor networks. The work considers static and mobile sensors. The mobile sensors case is the more interesting and difficult since it implies dynamic topology. We show how GA and PSO can be applied to optimize energy consumption in the sensor network and to maintain and re-organize the topology as sensors move.
The mobile sensors could be viewed as a crowd of people (e.g. carrying mobile telephones and participating in social networking). However, human swarms, unlike other swarms, are influenced in their behaviour by many factors such as perception, emotions and social relations. The second part of the talk will focus on emotions modeling. Emotions modeling reported in literature had often relied on threshold representation of emotions. In our work we start from psychological theories of emotion and develop computational models. This part of the talk will give a brief summary of the work done so far covering Darwinian / Ekman basic emotions, Millenson 3D model of emotions and Scherer wheel of emotions.
Some related publications
1. Blewitt , W.F., Ayesh, A.: Modeling the Emotional State of an Agent through Fuzzy Logic With Reference to the Geneva Emotion Wheel In: Bertelle, C., Ayesh, A. (eds.): European Simulation and Modelling (ESM'2008) Conference. EUROSIS, Le Havre, France (2008) 279-283
2. Blewitt, W., Ayesh, A., John, R.I., Coupland, S.: A Millenson-based approach to emotion modelling. Human System Interactions, 2008 Conference on (2008) 491-496
3. Al-Obaidy, M., Ayesh, A.: Optimizing Autonomous Mobile Sensors Network using PSO Algorithms. International Conference on Computer Engineering and Systems (ICCES'08). IEEE, Cairo, Egypt (2008)
4. Al-Obaidy, M., Ayesh, A.: Energy Efficient PSO-based Algorithm for Optimizing Autonomous Wireless Sensor Network In: Bertelle, C., Ayesh, A. (eds.): European Simulation and Modelling (ESM'2008) Conference. EUROSIS, Le Havre, France (2008) 201-206
5. Al-Hudhud, G., Ayesh, A.: Real Time Movement Coordination Technique Based on Flocking Behaviour for Multiple Mobile Robots System. Swarm Intelligence Algorithms and Applications Symposium (SIAAS'08) - AISB 2008 Convention, Vol. 11, Aberdeen, Scotland (2008) 31-37
6. Ayesh, A., Stokes, J., Edwards, R.: Fuzzy Individual Model (FIM) for Realistic Crowd Simulation: Preliminary Results. Fuzzy Systems Conference, 2007. FUZZ-IEEE 2007. IEEE International. IEEE, London (2007) 1-5
7. Ayesh, A.: Emotionally Motivated Reinforcement Learning Based Controller. IEEE SMC 2004, Vol. 1, The Hague, The Netherlands (2004) 874-878 vol. 871
8. Ayesh, A.: Perception and Emotion Based Reasoning: A Connectionist Approach. Informatica 27 (2003) 119-126
==============================
The talk will cover briefly two main research areas. The first part of the talk will look at current work undertaking to use swarm intelligence in optimizing sensor networks. The work considers static and mobile sensors. The mobile sensors case is the more interesting and difficult since it implies dynamic topology. We show how GA and PSO can be applied to optimize energy consumption in the sensor network and to maintain and re-organize the topology as sensors move.
The mobile sensors could be viewed as a crowd of people (e.g. carrying mobile telephones and participating in social networking). However, human swarms, unlike other swarms, are influenced in their behaviour by many factors such as perception, emotions and social relations. The second part of the talk will focus on emotions modeling. Emotions modeling reported in literature had often relied on threshold representation of emotions. In our work we start from psychological theories of emotion and develop computational models. This part of the talk will give a brief summary of the work done so far covering Darwinian / Ekman basic emotions, Millenson 3D model of emotions and Scherer wheel of emotions.
Some related publications
1. Blewitt , W.F., Ayesh, A.: Modeling the Emotional State of an Agent through Fuzzy Logic With Reference to the Geneva Emotion Wheel In: Bertelle, C., Ayesh, A. (eds.): European Simulation and Modelling (ESM'2008) Conference. EUROSIS, Le Havre, France (2008) 279-283
2. Blewitt, W., Ayesh, A., John, R.I., Coupland, S.: A Millenson-based approach to emotion modelling. Human System Interactions, 2008 Conference on (2008) 491-496
3. Al-Obaidy, M., Ayesh, A.: Optimizing Autonomous Mobile Sensors Network using PSO Algorithms. International Conference on Computer Engineering and Systems (ICCES'08). IEEE, Cairo, Egypt (2008)
4. Al-Obaidy, M., Ayesh, A.: Energy Efficient PSO-based Algorithm for Optimizing Autonomous Wireless Sensor Network In: Bertelle, C., Ayesh, A. (eds.): European Simulation and Modelling (ESM'2008) Conference. EUROSIS, Le Havre, France (2008) 201-206
5. Al-Hudhud, G., Ayesh, A.: Real Time Movement Coordination Technique Based on Flocking Behaviour for Multiple Mobile Robots System. Swarm Intelligence Algorithms and Applications Symposium (SIAAS'08) - AISB 2008 Convention, Vol. 11, Aberdeen, Scotland (2008) 31-37
6. Ayesh, A., Stokes, J., Edwards, R.: Fuzzy Individual Model (FIM) for Realistic Crowd Simulation: Preliminary Results. Fuzzy Systems Conference, 2007. FUZZ-IEEE 2007. IEEE International. IEEE, London (2007) 1-5
7. Ayesh, A.: Emotionally Motivated Reinforcement Learning Based Controller. IEEE SMC 2004, Vol. 1, The Hague, The Netherlands (2004) 874-878 vol. 871
8. Ayesh, A.: Perception and Emotion Based Reasoning: A Connectionist Approach. Informatica 27 (2003) 119-126
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