Police officer in-vehicle discomfort: Appointments carriage method and vehicle seat features

Musculoskeletal pain is commonly reported by police officers. A potential cause of officer discomfort is a mismatch between vehicle seats and the method used for carrying appointments. Twenty-five police officers rated their discomfort while seated in: (1) a standard police vehicle seat, and (2) a vehicle seat custom-designed for police use. Discomfort was recorded in both seats while wearing police appointments on: (1) a traditional appointments belt, and (2) a load-bearing vest/belt combination (LBV). Sitting in the standard vehicle seat and carrying appointments on a traditional appointments belt were both associated with significantly elevated discomfort. Four vehicle seat features were most implicated as contributing to discomfort: back rest bolster prominence; lumbar region support; seat cushion width; and seat cushion bolster depth. Authorising the carriage of appointments using a LBV is a lower cost solution with potential to reduce officer discomfort. Furthermore, the introduction of custom-designed vehicle seats should be considered.     

Estimating oxygen consumption from heart rate using adaptive neuro-fuzzy inference system and analytical approaches

In new approaches based on adaptive neuro-fuzzy systems (ANFIS) and analytical method, heart rate (HR) measurements were used to estimate oxygen consumption (VO₂). Thirty-five participants performed Meyer and Flenghi's step-test (eight of which performed regeneration release work), during which heart rate and oxygen consumption were measured. Two individualized models and a General ANFIS model that does not require individual calibration were developed. Results indicated the superior precision achieved with individualized ANFIS modelling (RMSE = 1.0 and 2.8 ml/kg min in laboratory and field, respectively). The analytical model outperformed the traditional linear calibration and Flex-HR methods with field data. The General ANFIS model's estimates of VO₂ were not significantly different from actual field VO₂ measurements (RMSE = 3.5 ml/kg min). With its ease of use and low implementation cost, the General ANFIS model shows potential to replace any of the traditional individualized methods for VO₂ estimation from HR data collected in the field.     

On the robust control of stable minimum phase plants with large uncertainty in a time constant. A fractional-order control approach

This paper addresses the problem of designing controllers that are robust to a great uncertainty in a time constant of the plant. Plants must be represented by minimum phase rational transfer functions of an arbitrary order. The design specifications are: (1) a phase margin for the nominal plant, (2) a gain crossover frequency for the nominal plant, (3) zero steady state error to step commands, and (4) a constant phase margin for all the possible values of the time constant (T$T$): 0<T<∞$0<T<\infty$. We propose a theorem that defines the structure of the set of controllers that fulfil these specifications and show that it is necessary for these robust controllers to include a fractional-order PI$PI$ term. Examples are developed for both stable and unstable plants, and the results are compared with a standard PI$PI$ controller and a robust controller designed using the QFT$QFT$ methodology.     

Smart pricing scheme: A multi-layered scoring rule application

Defining appropriate pricing strategy for smart environment is important and complex task at the same time. It holds the primal fraction in Demand Response (DR) program. In our work, we devise an incentive based smart dynamic pricing scheme for consumers facilitating a multi-layered scoring rule. The proposed strategy characterizes both incentive based DR and price based DR programs facilities. This mechanism is applied between consumer agents (CA) to electricity provider agent (EP) and EP to Generation Company (GENCO). Based on the Continuous Ranked Probability Score (CRPS), a hierarchical scoring system is formed among these entities, CA–EP–GENCO. As CA receives the dynamic day-ahead pricing signal from EP, it will schedule the household appliances to lower price period and report the prediction in a form of a probability distribution function to EP. EP, in similar way reports the aggregated demand prediction to GENCO. Finally, GENCO computes the base discount after running a cost-optimization problem. GENCO will reward EP with a fraction of discount based on their prediction accuracy. EP will do the same to CA based on how truthful they were reporting their intentions on device scheduling. The method is tested on real data provided by Ontario Power Company and we show that this scheme is capable to reduce energy consumption and consumers’ payment.     

ACE中设计模式在分布式网络服务中的应用研究

以网关应用服务的构建为例,详细探讨如何利用Acceptor-Connector模式来构建分布式网络服务的过程。通过分析其构造过程可知,利用Acceptor-Connector模式可提高程序的灵活性、可扩展性,减少重复开发代码工作量。     

基于Multi-Agent和HLA的口岸物流仿真

针对高层体系结构（ HLA）仿真建模技术的仿真联邦成员缺乏智能性和Multi-Agent仿真方法分布通信协同能力较差的问题。提出了一种集成两者的自适应中间件的方法,通过自适应中间件实现了两者集成的数据转换、通信及控制等功能,并进行实例验证。结果表明此方法在最小改变的情况下保证了集成开发的灵活性及方法的可行性、实用性和可靠性。     

网络结构增长的极端学习机算法

针对极端学习机(extreme learning machine,ELM)结构设计问题,基于隐含层激活函数及其导函数提出一种前向神经网络结构增长算法.首先以Sigmoid函数为例给出了一类基函数的派生特性:导函数可以由其原函数表示.其次,利用这种派生特性提出了ELM结构设计方法,该方法自动生成双隐含层前向神经网络,其第1隐含层的结点随机逐一生成.第2隐含层的输出由第1隐含层新添结点的激活函数及其导函数确定,输出层权值由最小二乘法分析获得.最后给出了所提算法收敛性及稳定性的理论证明.对非线性系统辨识及双螺旋分类问题的仿真结果证明了所提算法的有效性.     

基于TS201的信号处理软件设计

基于TS201处理器的软件优化设计,对于提高运算效率和运行稳定性是非常关键的。结合具体项目和实际工作经验,对如何正确利用TS201处理器的各种资源进行了分析,并提出了优化设计方法。按此方法设计的信号处理软件已成功应用到了某探测系统中,实现了系统提出的各种功能,并满足实时性要求,软件运行稳定,验证了所提方法的正确性。     

机车车载漏电流数字传感器研究与应用

介绍一种机车车载漏电流数字传感器的研究与应用,在模拟漏电流传感器的基础上,经数字化改进而实现.硬件设计采用ARM平台,在分析系统原理的基础上,完成了硬件系统和软件架构的设计,完成了单线和双线的模拟实验.经模拟实验验证检测准确、反应快速,通信采用CAN总线安全可靠.在实际测量中,验证了模拟实验的正确性,设计可行.     

基于网络统考课程的学习支持服务构建

为满足学生在网络统考课程学习中自主学习的需要,学习支持服务系统的研究、设计构建和有效运行至关重要。各试点高校关于网络统考学习支持服务的实践和做法很多,但系统性研究和理论总结不够,作者结合工作实际尝试构建了网络统考学习支持服务体系基本框架。