System Dynamics and Scenario Planning: Implementation Challenges

In this paper we discuss key implementation challenges of a systems approach that combines System Dynamics, Scenario Planning and Qualitative Data Analysis methods in tackling a complex problem. We present the methods and the underlying framework. We then detail the main difficulties encountered in designing and planning the Scenario Planning workshop and how they were overcome, such as finding and involving the stakeholders and customising the process to fit within timing constraints. After presenting the results from this application, we argue that the consultants or system analysts need to engage with the stakeholders as process facilitators and not as system experts in order to gain commitment, trust and to improve information sharing. They also need be ready to adapt their tools and processes as well as their own thinking for more effective complex problem solving.

Population genetic structure of the Yangtze finless porpoise (Neophocaena phocaenoides asiaeorientalis): Implications for management and conservation

Understanding the population genetic structure is a prerequisite for conservation of a species. The degree of genetic variability characteristic of the mitochondrial DNA control region has been widely exploited in studies of population genetic structure and can be useful in identifying meaningful population subdivisions. To estimate the genetic profile of the Yangtze finless porpoise (Neophocaena phocaenoides asiaeorientalis), an endangered freshwater population endemic to China, the complete mtDNA control region was examined in 39 individuals belonging to seven different stocks inhabiting the middle and lower reaches of the Yangtze River. Very low genetic diversity was found (nucleotide diversity 0.0011 +/- 0.0002 and haplotypic diversity 0.65 +/- 0.05). The mtDNA genetic pattern of the Yangtze population appears to indicate a founder event in its evolutionary history and to support the marine origin for this population. Analyses by F-st and Phi(st) yielded statistically significant population genetic structure (F-st = 0.44, P < 0.05; phi(st) = 0.36, P < 0.05). These results may have significant implications for the management and conservation of the Yangtze finless porpoise in the future.

Design and path planning for a remote-brained service robot

This paper presents a novel robot named "TUT03-A" with expert systems, speech interaction, vision systems etc. based on remote-brained approach. The robot is designed to have the brain and body separated. There is a cerebellum in the body. The brain with the expert systems is in charge of decision and the cerebellum control motion of the body. The brain-body. interface has many kinds of structure. It enables a brain to control one or more cerebellums. The brain controls all modules in the system and coordinates their work. The framework of the robot allows us to carry out different kinds of robotics research in an environment that can be shared and inherited over generations. Then we discuss the path planning method for the robot based on ant colony algorithm. The mathematical model is established and the algorithm is achieved with the Starlogo simulating environment. The simulation result shows that it has strong robustness and eligible pathfinding efficiency.

Design and path planning for a remote-brained service robot

This article introduced an effective design method of robot called remote-brain, which is made the brain and body separated. It leaves the brain in the mother environment, by which we mean the environment in which the brain's software is developed, and talks with its body by wireless links. It also presents a real robot TUT06-B based on this method which has human-machine interaction, vision systems, manipulator etc. Then it discussed the path planning method for the robot based on ant colony algorithm in details, especially the Ant-cycle model. And it also analyzed the parameter of the algorithm which can affect the convergence. Finally, it gives the program flow chat of this algorithm.