Mosaic models for textures

This paper deals with a class of image models based on random geometric processes. Theoretical and empirical results on properties of patterns generated using these models are summarized. These properties can be used as aids in fitting the models to images.     

Keyboard design through physiological strain measurements

The physiologically tolerable range of positions for the joints of the upper extremities have been investigated for typing tasks by recording the myoelectric activities of the involved muscles. For long-term typing tasks a split keyboard is recommended allocating a key field to each hand. The fields should be rotated against each other in the horizontal plane and inclined laterally.     

Advanced coded-aperture imaging system for nuclear medicine

An advanced coded imaging system is described, and some results of phantom experiments are presented. The advanced method uses a pair of coherent codes (+ 1 and -1 codes) and has many advantages compared with conventional ones. One of the greatest advantages is that there are no sidelobes in the focal plane and only a few in other planes. Therefore, when an object can be regarded as two-dimensional, it is perfectly reconstructed with high detecting efficiency, and this is successfully simulated by a thyroid phantom with 99mTc. Moreover, this system has an ability to reconstruct tomograms, which is also shown by using ring phantoms piled on one another with some cold spots in their shells. From these experimental results it may be concluded that the new system is useful for practical applications, for example, to nuclear medicine.     

加拿大农业和水资源管理案例研究

以南萨斯喀彻温河流域为例,对加拿大西部农业和水资源管理开展了研究,以便为改进水资源管理决策提供借鉴.该研究旨在评估由气候变化引起的水资源问题对社区发展造成的挑战,以及政府部门应对这些挑战的能力.概述了加拿大水资源管理政策及制度,并对该流域耗水大户——农业部门面临的水资源挑战开展了讨论.     

Simulation and stability analysis of neural network based control scheme for switched linear systems

This paper proposes a new adaptive neural network based control scheme for switched linear systems with parametric uncertainty and external disturbance. A key feature of this scheme is that the prior information of the possible upper bound of the uncertainty is not required. A feedforward neural network is employed to learn this upper bound. The adaptive learning algorithm is derived from Lyapunov stability analysis so that the system response under arbitrary switching laws is guaranteed uniformly ultimately bounded. A comparative simulation study with robust controller given in [Zhang L, Lu Y, Chen Y, Mastorakis NE. Robust uniformly ultimate boundedness control for uncertain switched linear systems. Computers and Mathematics with Applications 2008; 56: 1709-14] is presented.