Chain length of closed circle DNA is equal. The same closed circle DNA's position corresponds to different recognition sequence, and the same recognition sequence corresponds to different foreign DNA segment, so clos...Chain length of closed circle DNA is equal. The same closed circle DNA's position corresponds to different recognition sequence, and the same recognition sequence corresponds to different foreign DNA segment, so closed circle DNA computing model is generalized. For change positive-weighted Hamilton circuit problem, closed circle DNA algorithm is put forward. First, three groups of DNA encoding are encoded for all arcs, and deck groups are designed for all vertices. All possible solutions are composed. Then, the feasible solutions are filtered out by using group detect experiment, and the optimization solutions are obtained by using group insert experiment and electrophoresis experiment. Finally, all optimization solutions are found by using detect experiment. Complexity of algorithm is concluded and validity of DNA algorithm is explained by an example. Three dominances of the closed circle DNA algorithm are analyzed, and characteristics and dominances of group delete experiment are discussed.展开更多
文摘目的为提升人体工学椅的群体用户体验水平,从用户需求出发,研究产品的群体用户体验设计策略。方法首先,从白领人群对产品的行为特征、操作习惯和情感变化出发,结合唐·诺曼(Don Norman)提出的三层次理论,从欲望层次、行为层次和反应层次确定群体用户体验的关键评价指标,其次,应用提出的“概率密度有序加权”(Probability Density Ordered Weighting,PDOW)方法构建产品用户群体体验综合评价模型,克服用户体验测试的不确定性,并探寻用户群体评价结果与评价指标的联系。最后,设计白领人群人体工学椅产品用户体验实验,确定人体工学椅最佳方案。结果建模结果表明,应用综合评价模型,能够很好地反映出白领人群对人体工学椅外观、交互和情感的偏好,设计出用户体验更好的产品。结论“概率密度有序加权”方法可有效消除测试的不确定性,准确得出用户群体对产品的综合评价结果,其低成本、便捷高效的特性有助于产品设计过程中更好地了解用户群体的偏好,给产品设计中用户群体体验优化提供了新的解决思路。
基金supported by the National Natural Science Foundation of China(60574041)the Natural ScienceFoundation of Hubei Province(2007ABA407).
文摘Chain length of closed circle DNA is equal. The same closed circle DNA's position corresponds to different recognition sequence, and the same recognition sequence corresponds to different foreign DNA segment, so closed circle DNA computing model is generalized. For change positive-weighted Hamilton circuit problem, closed circle DNA algorithm is put forward. First, three groups of DNA encoding are encoded for all arcs, and deck groups are designed for all vertices. All possible solutions are composed. Then, the feasible solutions are filtered out by using group detect experiment, and the optimization solutions are obtained by using group insert experiment and electrophoresis experiment. Finally, all optimization solutions are found by using detect experiment. Complexity of algorithm is concluded and validity of DNA algorithm is explained by an example. Three dominances of the closed circle DNA algorithm are analyzed, and characteristics and dominances of group delete experiment are discussed.