Cognitive ergonomics of a mail order filling company: part 1 - influence of colour, position and highlighting on recognition time

Filling mail order request forms requires the picker to determine if the items ordered on the form are in his/her bay, reading the bin address and picking the item. An order form was investigated to determine if ergonomics improvements would result in improved productivity and accuracy. Colour, position and highlighting cues were systematically varied in a computer-simulated version of the picking task. It was concluded that colour and position significantly influence the processing time, while highlighting had no effect on processing time. Expert pickers were slower, but more accurate than the novine pickers. Recommendations for improving the order forms were made and implemented, with very encouraging results.     

Simulation-Based Construction of Three-Dimensional Process Model for Punching Cartridge Cases

A method of constructing three-dimensional process model for the punching cartridge cases is presented based on DEFORM simulation analysis.Using DEFORM software,the fmite element simulation models for the punching and forming process of cartridge cases are established,and the corresponding simulation result model of each intermediate procedure is obtained by continuously performing the forming process simulation.The simulation model cannot annotate size and process information due to poor interface between DEFORM software and CAD software.Thus,a 3D annotation module is developed with secondary development technology of UG NX software.Consequently,the final process model with dimension and process information is obtained.Then,with the current 3D process management system,the 3D punching and forming process design of cartridge cases can be completed further.An example is also provided to illustrate that the relative error between the simulation process model and the physical model is less than 2％,which proves the validity and reliability of the proposed method in this study.     

脉冲电源系统人机接口设计及实现

介绍一种以PIC16F77单片机为核心．采用图形点阵液晶显示模块VPG19264和编码键盘接口芯片MM74C922来实现脉冲电源系统人机接口设计方案。给出硬件接口电路原理图以及主程序软件流程图。     

大气细颗粒物与人体健康

本文讨论大气细颗粒物与人体健康问题。大气细颗粒物诱发人体癌症、心脏病,以及引起强烈的细胞毒性和遗传毒性。     

冲压机床的健康设计

“健康工业设计”这一设计理念充分体现了设计以人为本的思想,它在现代各种产品的设计中均有不同程度的体现。而现代机械锻压设备的设计还远远没有达到“健康工业设计”的要求,这里提出了现存冲压机床中存在的各种不健康因素,并且针对各因素提出了一些设计建议。     

加强人力资源开发与管理适应铁路运输生产发展

人力资源对企业发展至关重要，要改变传统管理方式向人力资源开发转变。面对新形势，应注重培养复合人才，并在物质基础上强调精神激励，尊重和宽容个性，充分实现个人的自身价值。建立适合铁路运输生产发展需求的人力资源开发与管理体系，使企业实现持续、跨越式发展。     

Representations in Human–Computer Systems Development

When system developers design a computer system (or other information artefact), they must inevitably make judgements as to how to abstract the domain and how to represent this abstraction in their designs. Over the years human–computer interaction, or more generally information systems design, has had a history of developing competing methods and models for both the process and products of its development. Various paradigms have been suggested, often trying to keep pace with the changing nature of the design problem; from batch processing to interactive systems to work situations and most recently to designing for household environments. It appears timely, then, to review the nature of the design problem that faces the developers of human–computer systems and to consider some of the impact that different representations and different conceptualisations may have on their activities. Green (1998) has suggested that a single model of developing human–computer systems is not desirable, instead arguing for a number of limited theories each of which provides a useful perspective. The aim of this paper is to place competing methods side by side in order to see their strengths and weaknesses more clearly. The central tenet of the paper is that different views of both the human–computer system design process and the different abstractions, or models, that are produced during the design process have varying degrees of utility for designers. It is unlikely that any single method or modelling approach will be optimal in all circumstances. Designers need to be aware of the range of views that exist and of the impact that taking a particular approach may have on the design solution.     

Intelligent assistance for older adults via an admittance-controlled wheeled mobile manipulator with task-dependent end-effectors

The increase in the ageing population worldwide poses a severe challenge in assisting older individuals to live independently, including the provision of mobility assistance and support in daily activities. In this paper, a practical robotic system is developed to provide intelligent support for older persons using a wheeled mobile manipulator (WMM), consisting of an omnidirectional mobile platform and a robotic arm. We focus on two critical needs: (1) mobility assistance, and (2) object manipulation support. The tasks are not executed simultaneously and each uses a task-dependent end-effector. Learning from demonstration, or kinesthetic teaching, is adopted to help the WMM to learn an elderly or disabled user’s walking pattern or an able-bodied person’s object manipulation skill. The robotic system can assist the user in conducting a number of daily operations. For mobility assistance, the WMM is reconfigured into a smart walker, where a novel variable admittance control is adopted to detect the user’s walking intention. A learning approach based on dynamic movement primitives is implemented to capture and adapt the WMM to the user’s walking pattern. For object manipulation support, a demonstrator first collaborates with an elderly user to conduct the task, and then the WMM takes the role of the demonstrator to assist the user. The Gaussian mixture model and Gaussian mixture regression are used to learn and reproduce the demonstrator’s experience, respectively. The advantages and effectiveness of the proposed approach are experimentally demonstrated with a four-wheel omnidirectional WMM.     

A survey on spatio-temporal framework for kinematic gait analysis in RGB videos

Human gait recognition from videos is one of the promising research topics for analyzing human walking behavior. Spatio-temporal features and kinematics interesting points (three dimensional skeleton points) are the two key metrics in the gait examination. In general, input to gait recognition methods is categorized into 3 groups namely; two dimensional video-based, depth image-based and three dimensional (3D) skeleton-based methods. This work aims to present a survey on spatio-temporal and kinematic gait characteristics based on visual and 3D skeletal traits in RGB videos. A detailed insight on the various benchmarked gait databases, gait recognition representations based on model-based, model-free approaches and classifiers are presented in this review. Also, this paper investigates the performance metrics, application areas and covariate factors that influence the gait recognition process. Finally, the paper outlines the future perspective of gait recognition system based on kinematic joint points.     

Hierarchical Learning-Guided human motion quality assessment in big data environment

Image information may be distorted during acquisition, processing, compression, and transmission. It is necessary to propose an intelligent image quality assessment model toward big data environment to quantify the degree of distortion of the image. This paper proposes a quality assessment model for human motion images. In complex scenes, the human body's action posture can be taken as an important feature point. Usually, in different scenes, the parts that affect the quality of the human body's posture are different. In other words, the weights of feature points that affect quality are different in different scenarios. However, due to the categorization of human movements, we can learn the quality assessment methods of different types of movements through sample training. Inspired by feature learning in the field of machine learning, we propose a hierarchical quality learning approach. We cast quality assessment as quality feature learning and layer by layer. The hierarchical quality learning method is based on deep reinforcement learning. The key part is that the method focuses on the region that containing more information on the features of the quality and enlarges the region layer by layer. Finally, we can determine the part of the body that affects the quality assessment. We compare this method with the subjective quality assessment results of the human observers and find that the proposed method achieves effective performance in big data environment to evaluate human motion quality.