Neural network based non-invasive method to detect anemia from images of eye conjunctiva

Detection of anemia can be done by examining the hemoglobin concentration level in the blood using complete blood count, which is an invasive, time-consuming, and costly technique. Preliminary methods for detecting anemia include examining the color of the palpebral conjunctiva, which is a non-invasive method, but color perception may vary from person to person. This study aims to develop a computerized non-invasive technique for anemia detection. We propose a novel machine learning model using the artificial neural network to detect anemic patients from the images of eye conjunctiva. Since limited and small dataset has been used in the earlier approaches, this may cause over fitting of the model. We have improved the number of available training images using image augmentation techniques. To standardize a non-invasive method, we have used computer vision algorithms for preprocessing and feature extraction. This article derives the backpropagation rules mathematically for adjusting the weights for the proposed neural network model. After hyper parameter tuning and using the mathematically derived backpropagation rules, the model was able to achieve the best accuracy of 97.00% with sensitivity 99.21% and specificity 95.42% on the created dataset.     

The introduction strategy of the emerging online marketplace considering risk attitude and channel power

With the development of online retailing, traditional online platforms have begun to offer a novel online marketplace format that brings many advantages but also gives rise to problems such as operational risks and changes in channel power. This paper studies whether the e-tailer and manufacturer can reach a consensus on introducing the marketplace channel and obtains the following insights. First, the manufacturer always prefers to introduce the online marketplace in the model where she acts as the leader. The e-tailer has the same preference for the online marketplace when he moves later or simultaneously with the manufacturer. Second, as the participants become more risk-averse, the manufacturer and e-tailer would be less willing to introduce the online marketplace, and it would be more difficult to realize the equilibrium strategy under all power structure models. Third, by combining the cross-effect of the attitude towards risks and the power structure, we find that when the participants prefer risks and the e-tailer has strong channel power, it would be much easier for the two parties to reach a consensus about introducing the online marketplace.     

不确定环境下基于质量功能展开的电动汽车技术特性综合重要度确定

电动汽车技术特性重要度的确定是电动汽车研发的关键环节,能协助研发主体优化资源配置,更好地满足顾客需求。综合考虑顾客需求、竞品情况、技术可得性情况以及企业自身实力情况,提出一种不确定环境下基于质量功能展开的电动汽车技术特性综合重要度确定模型,为电动汽车制造企业提供了一种科学、有效的开发工具。该模型利用基本不确定语言信息刻画不确定评估信息,模型的基本过程为:识别顾客需求,并利用最佳—最差权重确定方法(BWM)确定顾客需求重要度;确定顾客需求与技术特性关联关系,基于顾客需求重要度确定技术特性基本重要度;利用BWM方法,确定基于竞品分析的修正重要度、基于技术可得性的修正重要度以及基于自身实力的修正重要度;综合基本重要度与修正重要度,确定技术特性综合重要度。最后,以某一企业的电动汽车研发案例为对象,论证了该模型的可行性与有效性。     

A coupled and interactive influence of operational parameters for optimizing power output of cleaner energy production systems under uncertain conditions

The mechanisms in proton‐exchange membrane fuel cells (PEMFCs) cannot be explicitly represented by a mathematical function because the PEMFC system is multi‐dimensional and complex and represents uncertainty in operation variables, which cannot be modeled by experiments or by trial‐and‐error approach. Therefore, this work proposes to study the coupled and interactive influence of stack current (SC), stack temperature (ST), oxygen excess ratio (OER), hydrogen excess ratio (HER), and inlet air humidity (IAH) for optimizing the power output of PEMFC. The data obtained from the experiments have been inserted into architecture of automated neural‐network search, which automates the selection of error function, activation function, uncertainties in inputs and number of hidden neurons in formulation of a robust and accurate model for power density as a function of five operational variables. Among the operational variables, the correlation coefficient between the SC and the output power is the highest, followed by OER, and the ST. However, for HER and IAH, the power output follows negative nonlinear relation. The optimization converged at 130^th iteration results in maximum power output of 3410 W for an optimum value of SC (51A), ST (59°C), OER (3:2), HER (1:10), and IAH (0.8).     

Engineering knowledge formalization and proposition for informatics development towards a CAD-integrated DfX system for product design

Target design methodologies (DfX) were developed to cope with specific engineering design issues such as cost-effectiveness, manufacturability, assemblability, maintainability, among others. However, DfX methodologies are undergoing the lack of real integration with 3D CAD systems. Their principles are currently applied downstream of the 3D modelling by following the well-known rules available from the literature and engineers’ know-how (tacit internal knowledge).This paper provides a method to formalize complex DfX engineering knowledge into explicit knowledge that can be reused for Advanced Engineering Informatics to aid designers and engineers in developing mechanical products. This research work wants to define a general method (ontology) able to couple DfX design guidelines (engineering knowledge) with geometrical product features of a product 3D model (engineering parametric data). A common layer for all DfX methods (horizontal) and dedicated layers for each DfX method (vertical) allow creating the suitable ontology for the systematic collection of the DfX rules considering each target. Moreover, the proposed framework is the first step for developing (future work) a software tool to assist engineers and designers during product development (3D CAD modelling).A design for assembly (DfA) case study shows how to collect assembly rules in the given framework. It demonstrates the applicability of the CAD-integrated DfX system in the mechanical design of a jig-crane. Several benefits are recognized: (i) systematic collection of DfA rules for informatics development, (ii) identification of assembly issues in the product development process, and (iii) reduction of effort and time during the design review.     

Impact of regulatory rules on economic performance of PV power plants

The rapid growth of Renewable Energy Sources (RES) power plants connected to the grid has introduced new problems related to the safe and reliable operation of the electricity network from transmission to distribution sectors. New regulatory rules can promote RES producers to make a commitment on the energy amount that is likely to be supplied to the network. The present paper concerns the analysis of the energy production of a PV power plant from the economic point of view, with reference to the presence of regulatory rules. Costs of penalty and value of energy are compared, in order to evaluate the economic efficiency of the plant. Use of auxiliary energy storage devices is investigated, with the aim to determine the relevant dimensions that increase the economic efficiency of the PV plant. A software instrument that implements these algorithms is described and applied to a case study.     

分子轨道方法在有机反应机理中的应用

利用分子轨道理论直观解释了有机反应机理中所涉及到的立体化学、区域选择性以及对称性选择规律等有机化学中不易解释清楚的问题。相较于传统的"电子推动"方法,分子轨道方法更加直观,并能为有机反应机理的学习提供更深的理解。     

基于改进粒子群算法的线缆路径规划方法研究

针对复杂机电产品布线路径规划过程中存在的效率较低、可应用性差等问题,提出一种改进粒子群算法,使用栅格法对布线空间进行划分,对障碍物建模并进行方向包围盒处理。为了避免算法在迭代过程中陷入局部最优,引入非线性逐渐递减的惯性权重与异步变化的学习因子,并且将贴壁约束加入到路径规划的过程中,保证线缆在敷设时路径的合理性。最后在仿真试验中,与标准粒子群算法进行对比,验证了改进后算法的合理性与可行性。     

地下工程力学综合集成智能分析的理论和方法

应用人工智能、神经网络等新兴学科理论，提出了地下工程力学综合集成智能的分析方法。着重探讨了地下工程力学综合集成智能分析的基本模型、智能岩层控制系统模型、一种新的不确定性推理方法、岩体区域等价本构模型的自适应识别新方法。初步工程实践表明，它具有先进性和科学性，可以应用于处理复杂的岩石工程问题。     

基于修正Masing准则的萧山软黏土动应力-应变关系研究

地震、波浪、交通等不排水循环荷载的作用将引起土体孔隙水压力上升,从而使土体的刚度、强度发生软化现象,以往对软粘土动应力-应变关系的研究大都忽略循环软化的影响。采用Masing准则及其修正来描述软黏土的动应力-应变关系往往与实际偏差较大,主要是因为该准则未能考虑软黏土的循环软化特性。通过对萧山软黏土进行应力控制的循环三轴试验,研究循环次数、循环应力、偏应力对萧山软黏土的循环软化特性的影响。通过对每次循环中的刚度进行无量纲化得到量纲一的刚度Gsec/Gmax与循环应变幅值εs的关系曲线。研究结果表明,当循环应力较小时,Gsec/Gmax-εs曲线由硬化及软化两部分组成;当循环应力大于58kPa时,该曲线仅表现为软化特性。在试验基础上得到量纲一的刚度软化模型,该模型可体现每次循环过程中的刚度软化规律。同时,基于修正的Masing准则,结合循环软化模型,得到考虑循环软化特性的萧山软黏土动应力-应变关系曲线。