基于改进GSO的裂解炉原料切换策略研究(英文)

The scheduling process of cracking furnace feedstock is important in an ethylene plant. In this paper it is described as a constraint optimization problem. The constraints consist of the cycle of operation, maximum tube metal temperature, process time of each feedstock, and flow rate. A modified group search optimizer is pro-posed to deal with the optimization problem. Double fitness values are defined for every group. First, the factor of penalty function should be changed adaptively by the ratio of feasible and general solutions. Second, the“excel-lent”infeasible solution should be retained to guide the search. Some benchmark functions are used to evaluate the new algorithm. Final y, the proposed algorithm is used to optimize the scheduling process of cracking furnace feedstock. And the optimizing result is obtained.     

基于STM32单片机的大学生体能监测仪设计与实现

体能监控仪作为生命体征监测设备,对于辅助大学生完成体能训练有很大帮助;基于STM32单片机技术,设计开发集成了多种传感器的一种大学生体能监测装备,它能够有效的检测包括心率检测、人体的步数、运动圈速、消耗卡路里等信息;该设计采用了STM32作为主控芯片,采用模块化的设计思路;在系统硬件设计方面,设计了包括STM32控制系统、心率获取电路、三轴传感器电路、显示电路以及按键电路等;同时将软件模块拆分成了初始化子程序、心率获取子程序,步数获取子程序,显示子程序等;Proteus仿真结果显示,使用STM32单片机技术设计的体能监测系统,能够运行稳定,测量心率范围60次/min~180次/min,可在心率异常时报警,同时检测步数的准确率达98%,满足体能监测任务需要,实验结果符合预期;为STM32单片机在体育运动研究信息化中应用提供参考。     

东方学院教学楼设计的探讨

面对我国高校教育的不断改善与提高,教育建筑呈现蓬勃发展之势。文章结合实际 (黑龙江省东方学院)工程项目,总结设计经验,希望对我国现阶段教学楼的设计起到一些作用。     

城市公园体育健身功能更新探索——以北京市 海淀区为例

为响应全民健身战略与体育强国建设政策,从用地 比例、项目内容两方面,提出不同类别城市公园体育健身功能 的更新策略。1)以北京城市公园为例,分析当前公园绿地体 育健身功能现状,明晰问题。2)对比国内外一线地区公园体 育健身功能建设,寻找差距。3)综合国内外优秀建设经验, 将公园分为三大类：游园和社区公园(小于5hm2 )、社区公园 和小型综合公园(5~20hm2 )、大型综合公园和郊野公园(大于 20hm2 ),分别提出更新策略。分析得出,城市公园用地具备 承载更多体育健身功能的潜力。应对公园建设情况进行灵活评 估,适度提升体育健身用地比例,并根据公园规模、使用者年 龄结构等要素,丰富公园用地所承载的体育健身项目内容。     

Progressive filling partitioning and mapping algorithm for Spark based on allocation fitness degree

The job execution mechanism of Spark was analyzed,task efficiency model and Shuffle model were established,then allocation fitness degree (AFD) was defined and the optimization goal was put forward.On the basis of the model definition,the progressive filling partitioning and mapping algorithm (PFPM) was proposed.PFPM established the data distribution scheme adapting Reducers’ computing ability to decrease synchronous latency during Shuffle process and increase cluster the computing efficiency.The experiments demonstrate that PFPM could improve the rationality of workload distribution in Shuffle and optimize the execution efficiency of Spark.     

Driving behaviors in early stage dementia: A study using in-vehicle technology

According to the Alzheimer's Association (2011), (1) in 8 people age 65 and older, and about one-half of people age 85 and older, have Alzheimer's disease in the United States (US). There is evidence that drivers with Alzheimer's disease and related dementias are at an increased risk for unsafe driving. Recent advances in sensor, computer, and telecommunication technologies provide a method for automatically collecting detailed, objective information about the driving performance of drivers, including those with early stage dementia. The objective of this project was to use in-vehicle technology to describe a set of driving behaviors that may be common in individuals with early stage dementia (i.e., a diagnosis of memory loss) and compare these behaviors to a group of drivers without cognitive impairment. Seventeen drivers with a diagnosis of early stage dementia, who had completed a comprehensive driving assessment and were cleared to drive, participated in the study. Participants had their vehicles instrumented with a suite of sensors and a data acquisition system, and drove 1–2 months as they would under normal circumstances. Data from the in-vehicle instrumentation were reduced and analyzed, using a set of algorithms/heuristics developed by the research team. Data from the early stage dementia group were compared to similar data from an existing dataset of 26 older drivers without dementia. The early stage dementia group was found to have significantly restricted driving space relative to the comparison group. At the same time, the early stage dementia group (which had been previously cleared by an occupational therapist as safe to drive) drove as safely as the comparison group. Few safety-related behavioral errors were found for either group. Wayfinding problems were rare among both groups, but the early stage dementia group was significantly more likely to get lost.     

An interactive genetic algorithm with the interval arithmetic based on hesitation and its application to achieve customer collaborative product configuration design

Complex product configuration design requires rapid and accurate response to customers’ demand. The participation of customers in product design will be a very effective solution to achieve this. The traditional interactive genetic algorithm (IGA) can solve the above problem to some extent by a computer-aided user interface. However, it is difficult to adopt an accurate number to express an individual's fitness because the customers’ cognition of evolutionary population is uncertain, and to solve the users’ fatigue problem in IGA. Thus, an interactive genetic algorithm with interval individual fitness based on hesitancy (IGA-HIIF) is proposed in this paper. In IGA-HIIF, the interval number derived from users’ evaluation time is adopted to express an individual's fitness, and the evolutionary individuals are compared according to the interval probability dominant strategy proposed in this paper. Then, the genetic operations are applied to generate offspring population and the evolutionary process doesn’t stop until it meets the termination conditions of the evolution or user manually terminates the evolution process. The IGA-HIIF is applied into the design system of the car console configuration, and compared to the other two kinds of IGA. The extensive experiment results are provided to demonstrate that our proposed algorithm is correct and efficient.     

粒子群阵列天线方向图适应值函数研究

在粒子群算法优化阵列天线方向图时,适应值函数的选取对算法收敛和优化效率都有着至关重要的影响。针对复杂多指标方向图优化容易早熟收敛,提出了一种分步的适应值函数策略,通过分阶段提高优化指标,可以更好地促进算法收敛和提升优化效率。仿真结果表明:将此适应值策略应用于天线方向图综合中,在不改变算法本身的同时,可以在多零点和低旁瓣约束情况下取得更好的优化效果。