谈“启发障碍法”在诊断学教学中应用

谈“启发障碍法”在诊断学教学中应用张玉东（附属第一医院循环科）诊断学是一门重要的临床基础课。其症状复杂、名称繁多，而且内容缺乏连惯性、系统性，因此对于每个教师与学生来说如何教好与学好都是一个难题。为使学生在有效时间内掌握这门课程，笔者在传统教学方法基...

需求问题根源需求启发技术

表达了这样一个要开发的系统的需求：“值班人员”需要使用系统来达到“派单”的目的．或者说，“派单”是系统应该为值班人员提供的一种价值。但问题来了：我们怎么知道“值班人员”使用系统来“派单”是一个合适的需求?答案只能来自涉众．和“派单”这个事情利益相关的人们。

A Real-Time Collision-Free Path Planning of a Rust Removal Robot Using an Improved Neural Network

In this paper, a real-time collision-free path planning of the rust removal robot in a ship environment is proposed, which is based on an improved biologically inspired neural network algorithm. This improved algorithm is based on the biologically inspired neural network and modified with obstacle detection sensors and kinematic state templates, and is implemented in a ship rust removal robot planning system for dynamic trajectory generation. The real-time optimal trajectory is generated by the biologically inspired neural network, and the moving obstacle detection process of a ship robot working on the wall is simulated with the obstacle detection sensors models. The local real-time trajectory can be re-planned by the updated local map information, where the obstacle detection sensors are used to inspect partial environment information and update the robot nearby information in real time in the original neural network algorithm. At the same time, the method of the kinematic state templates matching and searching is used to solve the pipes’ influence of the rust removal robot climbing on the wall, which can not only provide a smooth path, but also can judge the motion direction and turning angle of the robot. Comparison of the proposed approach with the simulation shows that the improved algorithm is capable of planning a real-time collision-free path with achieving the local environmental information and judging the rust removal robot’s motion direction and turning angle. This proposed algorithm can be good used in the ship rust removal robot. © 2017, Shanghai Jiaotong University and Springer-Verlag GmbH Germany.