Aggregation-induced emission luminogen-assisted stimulated emission depletion nanoscopy for super-resolution mitochondrial visualization in live cells

Nano Research - Aggregation-induced emission luminogens (AIEgens) are fluorescent agents that are ideal for bioimaging and have been widely used for organelle targeting, cellular mapping, and...     

构建信息对抗专业的知识体系和实践教学体系

针对我校信息对抗技术专业的发展方向和培养定位,结合我校办学特色,提出该专业的知识体系和实践教学体系。通过对当前现状和存在问题的分析,研究探讨符合实际的专业教学和人才培养模式。     

Anybus串行网关在HOLLIAS MACS系统Profibus现场总线中的应用

介绍Anybus串行网关在石西油田油气处理站HOLLIASMACS系统中的应用。     

WBMOAIS: A novel artificial immune system for multiobjective optimization

This study presents a novel weight-based multiobjective artificial immune system (WBMOAIS) based on opt-aiNET, the artificial immune system algorithm for multi-modal optimization. The proposed algorithm follows the elementary structure of opt-aiNET, but has the following distinct characteristics: (1) a randomly weighted sum of multiple objectives is used as a fitness function. The fitness assignment has a much lower computational complexity than that based on Pareto ranking, (2) the individuals of the population are chosen from the memory, which is a set of elite solutions, and a local search procedure is utilized to facilitate the exploitation of the search space, and (3) in addition to the clonal suppression algorithm similar to that used in opt-aiNET, a new truncation algorithm with similar individuals (TASI) is presented in order to eliminate similar individuals in memory and obtain a well-distributed spread of non-dominated solutions. The proposed algorithm, WBMOAIS, is compared with the vector immune algorithm (VIS) and the elitist non-dominated sorting genetic system (NSGA-II) that are representative of the state-of-the-art in multiobjective optimization metaheuristics. Simulation results on seven standard problems (ZDT6, SCH2, DEB, KUR, POL, FON, and VNT) show WBMOAIS outperforms VIS and NSGA-II and can become a valid alternative to standard algorithms for solving multiobjective optimization problems.     

Multi-agent and driving behavior based rear-end collision alarm modeling and simulating

Distance-between-vehicle-measurement is the only factor in traditional car rear-end alarm system. To address the above problem, this paper proposes an alarming model based on multi-agent systems (MAS) and driving behavior. It consists of four different types of agents that can either work alone or collaborate through a communications protocol on the basis of the extended KQML. The rear-end alarming algorithm applies the Bayes decision theory to calculate the probability of collision and prevent its occurrence real-time. The learning algorithm of driving behavior based on ensemble artificial neural network (ANN) and the decision procedure based on Bayes’ theory are also described in this paper. Both autonomy and reliability are enhanced in the proposed system. The effectiveness and robustness of the model have been confirmed by the simulated experiments.     

教学科研实践一体化,知识能力素质齐增长——软件工程专业实践创新教学改革探索

<正>加强学生工程实践能力的培养是高校工科教育改革的重要内容,其中培养学生的科研实践能力是教学改革和科研实践的重要组成部分。软件工程专业是国家示范性软件学院率先设立的面向工业界培养软件工程师的专业,因此对实践能力的要求更高。华东师范大学软件学     

用组态王开发钢包精炼炉监控系统

运用"Kingview 6.53"组态软件的强大功能开发了钢包精炼炉监控系统,以实现对电极、高压、冶炼、液压、氩气、冷却等各个系统运行状况的实时监控、故障报警、数据报表趋势分析与打印、历史数据记录及查询等功能.该系统图形界面友好、数据采集实时性好且准确可靠、操作方便、安全稳定.