Technical note. Computer-aided human modelling programs for workstation design

In designing a workstation, computer-aided human modelling programs can be used advantageously to analyse human-fit to the workstation components. The analysis is performed within a three-dimensional computer graphics environment. To illustrate the current state of development, six representative programs were selected: CYBERMAN, COMBIMAN, CREW CHIEF, JACK, SAMMIE, and MANNEQUIN. The programs differ considerably in terms of system requirement, operating characteristics, applicability and the various ergonomic evaluation functions available in the human modelling programs. The comparative analysis of the programs will aid the user to select the appropriate program for a particular workstation design.     

Finite element simulations of static and sliding contact between a human fingertip and textured surfaces

This paper presents a mechanics study of the variations with position and time of stresses within the dermis and epidermis of a human fingertip when it is loaded and slid over textured surfaces. Its purpose is to examine how fingerprints interact with surface texture to cause stress variations in tune with the sensitivities of Meissner and Pacinian corpuscles through which humans in part interpret tactile sensations. A two-dimensional multilayer elastic finite element model of a fingertip has been created for this purpose. Results show that fingertip’s epidermal ridges have little effect on stress distribution within the fingertip in static loading but significantly increase stress oscillations during sliding over a textured surface. Oscillation frequencies from the sliding simulations are in ranges that should stimulate a fingertip’s Meissner and Pacinian corpuscle nerve endings.     

Seeker optimization algorithm for global optimization: A case study on optimal modelling of proton exchange membrane fuel cell (PEMFC)

In order to optimize the proton exchange membrane fuel cell (PEMFC) model parameters, a novel approach based on seeker optimization algorithm (SOA) is proposed. The SOA is based on the concept of simulating human searching behaviors, where the choice of search direction is based on the empirical gradient by evaluating the response to the position changes and the decision of step length is based on uncertainty reasoning by using a simple Fuzzy rule. In this study, after evaluated on benchmark function optimization, the SOA is applied to optimal modelling of the PEMFC by using a fuel cell test system in Fuel Cell Application Centre (FAC) at the Temasek Polytechnic, and compared with several state-of-the-art versions of differential evolution (DE) and particle swarm optimization (PSO) algorithms. The simulation results show that the proposed approach is superior to other compared algorithms, and the PEMFC model with optimized parameters by SOA fitted experimental data well. Hence, SOA is an effective and reliable technique for optimizing the parameters of PEMFC model, and can be helpful for system analysis, optimization design and real-time control of the PEMFCs.     

Shared human–robot path following control of an unmanned ground vehicle

This paper considers the shared path following control of an unmanned ground vehicle by a single person. A passive measure of human intent is used to blend the human and machine inputs in a mixed initiative approach. The blending law is combined with saturated super-twisting sliding mode speed and heading controllers, so that exogenous disturbances can be counteracted via equivalent control. It is proven that when the proposed blending law is used, the combined control signals from both the human and automatic controller respect the actuator magnitude constraints of the machine. To demonstrate the approach, shared control experiments are performed using an unmanned ground vehicle, which follows a lawn mower pattern shaped path.     

No-Reference Video Quality Assessment using novel hybrid features and two-stage hybrid regression for score level fusion

This paper presents a novel No-Reference Video Quality Assessment (NR-VQA) model that utilizes proposed 3D steerable wavelet transform-based Natural Video Statistics (NVS) features as well as human perceptual features. Additionally, we proposed a novel two-stage regression scheme that significantly improves the overall performance of quality estimation. In the first stage, transform-based NVS and human perceptual features are separately passed through the proposed hybrid regression scheme: Support Vector Regression (SVR) followed by Polynomial curve fitting. The two visual quality scores predicted from the first stage are then used as features for the similar second stage. This predicts the final quality scores of distorted videos by achieving score level fusion. Extensive experiments were conducted using five authentic and four synthetic distortion databases. Experimental results demonstrate that the proposed method outperforms other published state-of-the-art benchmark methods on synthetic distortion databases and is among the top performers on authentic distortion databases. The source code is available at https://github.com/anishVNIT/two-stage-vqa.     

PS在发现人为失误中的应用

在人们的日常生活中和生产活动中，安全管理和品质管理日趋重要，提高PS意识作为一种新兴的管理理念和手法，被越来越多的企业所采用，无论是作为一种工作态度还是一种生活习惯逐渐被人们所接受。本文对PS的概念、人为失误实质剖析、减少及发现人为失误中PS的运用进行了阐述。     

人体胃肠道智能仿生系统设计

消化系统是人体构成的重要系统之一,食物的消化与吸收给人体源源不断地提供能量,促使其他系统正常运转,这是一个相当繁琐的过程,因此所产生的胃肠道疾病也是错综复杂,传统的胃肠道疾病的诊断和治疗主要采用胃肠道内窥镜,这个过程是相当痛苦的。而传统的医学研究大多采用活体(小白鼠)进行实验,但这又不符合人道主义。所以本文建立了一个能够在离体条件下直观地模拟胃肠道工作的系统。     

A weighted full-reference image quality assessment based on visual saliency

In full reference image quality assessment (IQA), the images without distortion are usually employed as reference, while the structures in both reference images and distorted images are ignored and all pixels are equally treated. In addition, the role of human visual system (HVS) is not taken account into subjective IQA metric. In this paper, a weighted full-reference image quality metric is proposed, where a weight imposed on each pixel indicates its importance in IQA. Furthermore, the weights can be estimated via visual saliency computation, which can approximate the subjective IQA via exploiting the HVS. In the experiments, the proposed metric is compared with several objective IQA metrics on LIVE release 2 and TID 2008 database. The results demonstrate that SROCC and PLCC of the proposed metric are 0.9647 and 0.9721, respectively,which are higher than other methods and it only takes 427.5 s, which is lower than that of most other methods.     

双目立体视频最小可辨失真模型及其在质量评价中的应用

该文针对目前最小可辨失真(JND)模型只能应用于评价单视点视频的问题,探索一种以双眼亮度关系为基本出发点的双目立体视频的JND模型。首先根据立体视频特性引入双眼亮度关系模型,然后考虑了背景亮度掩盖、纹理掩盖、帧间掩盖、空间时间对比灵敏度、眼睛运动等因素,提出了双目JND模型,最后将该双目JND模型应用到立体视频质量评价方法中。实验结果表明该文提出的质量评价方法符合人类的视觉感知特性,更接近于主观测试结果。     

引入语义部位约束的行人再识别

为减轻行人图片中的背景干扰,使网络着重于行人前景并且提高前景中人体部位的利用率,该文提出引入语义部位约束(SPC)的行人再识别网络。在训练阶段,首先将行人图片同时输入主干网络和语义部位分割网络,分别得到行人特征图和部位分割图;然后,将部位分割图与行人特征图融合,得到语义部位特征;接着,对行人特征图进行池化得到全局特征;最后,同时使用身份约束和语义部位约束训练网络。在测试阶段,由于语义部位约束使得全局特征拥有部位信息,因此测试时仅使用主干网络提取行人的全局信息即可。在大规模公开数据集上的实验结果表明,语义部位约束能有效使得网络提高辨别行人身份的能力并且缩减推断网络的计算花费。与现有方法比较,该文网络能更好地抵抗背景干扰,提高行人再识别性能。