No abstract

No abstract

structed from a large number of discrete modules. Each module is capable of being connected to one or more modules. While the capabilities of a single module with one active degree of freedom are modest, the combination can form arbitrarily complex structures. With enough modules a robot of arbitrary complexity be achieved. As well, a huge number of radically different robots can be constructed with the same set of modules. With each form change, there are concomitant changes in properties and capabilities. For example, one MRR might have six legs (classic insect-style legged motion) while keeping a sensor payload stable. Should the need arise, it could form a snake, capable of crawling through cracks and pipes. This modularity allows for potential cost savings, due to economies of scale and

Abstract:In developing countries, land productivity involves little market, where the agricultural land use is mainly determined by the food demands as well as the land suitability. The land use pattern will not ensure everywhere enough land for certain cropping if spatial allocation just according to land use suitability. To solve this problem, a subzone and a pre-allocation for each land use are added in spatial allocation module, and land use suitability and area optimization module are incorporated to constitute a whole agricultural land use optimal allocation (ALUOA) system. The system is developed on the platform .Net 2005 using ArcGIS Engine (version 9.2) and C# language, and is tested and validated in Yili watershed of Xinjiang Region on the newly reclaimed area. In the case study, with the help of soil data obtained from 69 points sampled in the fieldwork in 2008, main river data supplied by the Department of Water Resources of Xinjiang Uygur Autonomous Region in China, and temperature data provided by Data Center for Resources and Environmental Sciences, Chinese Academy of Sciences, land use suitability on eight common crops are evaluated one by one using linear weighted summation method in the land use suitability model. The linear programming (LP) model in area optimization model succeeds to give out land area target of each crop under three scenarios. At last, the land use targets are allotted in space both with a six subzone file and without a subzone file. The results show that the land use maps with a subzone not only ensure every part has enough land for every crop, but also gives a more fragmental land use pattern, with about 87.99% and 135.92% more patches than the one without, while at the expense of loss between 15.30% and 19.53% in the overall suitability at the same time.