基于用户行为的产品开发研究

从需求多样化的消费者与纷繁复杂的产品开发现实出发,提出了"基于用户行为的产品开发"这一创新理念;分析了用户行为过程在完成优秀产品开发中的地位和重要性,发展了两者关系;通过对多个创新设计案例的归类与分析,从单个用户行为到多个用户行为的系统整合,探讨了基于用户行为分析的理念、思路与方法,为设计师创造令人值得期待的产品提供了一种创新的研究思路。     

大规模协同产品开发过程多主体建模及仿真研究

首先建立了基于主体行为的大规模协同产品开发过程仿真模型,模型包含多主体行为模型和环境对象两大部分;其次,描述了多主体过程仿真模型的交互过程,设计开发了大规模协同产品开发过程仿真系统;最后,基于仿真系统对大规模协同产品开发过程进行了关于设计者动态特性、社区规模及社区演化的仿真实验分析。实验结果表明,基于主体行为的大规模协同产品开发过程仿真模型及仿真系统可有效地从主体、产品和社区的角度描述实际的大规模协同产品开发过程。     

产品开发过程中的标准化

一、产品开发过程中企业标准化工作的事要任务 任何新产品的构思都需要经过后续的开发活动来实现,产品开发是一个由众多部门和人员参加的系统过程．需要各部门的通力合作与密切配合。产品开发计划的实施又是一个不断调整和修正的动态过程。产品开发过程中的标准化工作是保证开发成果符合设计构思、保证产品性能满足用户需要的重要保障。其主要任务是：     

浅议创建“标准化良好行为企业”

本文介绍了在经济全球化的背景之下,企业创建"标准化良好行为"的重要意义,在推进过程中采取的有效措施及开展此项工作的具体做法。并结合当前我国企业标准化工作现状,初步探讨了企业应对全球经济危机的新思路。     

文创产品的综合评价与购买行为关系研究

目的 探析当代大学生群体对文创产品的评价态度与购买行为动机之间的关系。方法 通过问卷调查,以统计学的方法分析论证了“吸引大学生群体购买文创产品的内在原因”。结论 在影响这一群体购买文创产品的7个要素中,“文化创意”并不是其做出购买行为决策的最主要原因（其卡方值为10.56*）,而其中产品的“性价比”（其卡方值为21.33***）与“使用功能（卡方值为18.40**）”在其购买决策过程中则表现出了更加重要的影响。本结论可引发文创工作者对文创产品的内在价值进行再思考,也能为特定用户的文创产品开发设计带来有益的启示。     

从业人员的不安全心理行为探析

从业人员因为不安全行为因素是导致各类事故发生重要原因之一．如何具备良好、稳定的安全心理状态进而引导合理的安全行为．本文针对从业人员的不安全心理行为等因素进行分析探讨。     

空间信息的呈现界面对建筑火灾中寻路行为的影响

为了提高危机救援过程中团体内部与外部的空间共享效率,结合建筑火灾的动态建筑结构变化与人类空间信息的认知表征、空间信息的交互方式,设计了两种空间信息界面:静态朝向信息一致信息界面;动态朝向信息一致信息界面,探究动态环境中不同朝向信息对于寻路绩效的影响。通过Unity3D软件模拟实际空间环境的动态变化,采集虚拟环境中内部人员的寻路行为,并通过录像与访谈分析建筑内外人员的交互行为。实验结果表明:1)静态信息界面下寻路时间与路径更短,寻路过程中的错误路径更少,但交互行为更多。2)动态信息界面下寻路时间与路径更长,寻路过程中交互行为更少,但错误路径更多。研究结果可以为消防救援队伍的内外协同提供支持,提升救援效率。     

心理危机干预体系中的应对能力教育

近年来大学生心理危机事件频频发生,加强大学生心理危机干预体系建设力度追在眉睫。本研究从心理危机干预预警和和应对角度出发,探讨如何通过应对能力的培养减少心理危机事件的发生,并在此基础上提出心理危机干预体系中的应对能力培养的措施。     

基于用户行为的产品设计原则

目的指导设计师设计出能够便利、引导或者约束用户行为的产品。方法通过分析相关案例,归纳出了行为相符、行为相关、行为相似以及行为相悖4个设计原则,并探讨了相应的设计方法和思路。结论行为相符原则满足用户的生理要求,设计师要考虑用户和产品互动过程中的人机数据;行为相关原则满足用户便利的需求,设计师要挖掘和产品有关的用户行为,通过功能复合提供更周全的服务;行为相似原则满足行为方式的传承与认同,设计师要挖掘处于某种文化脉络中的用户行为习惯,设计出吻合用户的操作习惯和满足他们的情感体验的产品;行为相悖原则是防止用户不当行为,设计师要通过设计打断某些行为的连续性,对用户的某些不安全行为进行约束。     

β-Sialon-Nd-黄长石固溶体材料的生成和氧化行为

研究了在β10－Sialon（Si5．23Al0.77O0．77N7，23）中加入7．26Wt％Nd-黄长石固溶体（Nd2Si2AlO4N3）组份的反应过程和致密化行为．烧结过程中，稀土元素先进入α－Sialon；随温度的升高，稀土元素存在于晶界玻璃相中，并在退火过程中以黄长石相析出．对热压及经退火处理的样品，研究了其在1000～1400℃的氧化行为．1000℃氧化时，作为晶界相的黄长石固溶体并不会导致样品开裂．但在更高温度氧化时，氧化后的表面存在择优取向的A－Nd2Si2O7晶粒，且由于Nd离子的表面偏析使表面氧化层软化而形成气泡．     

A Proactive Operational Framework for Business Continuity in the Semiconductor Industry

Prolonged disruption due to a man‐made crisis or a natural disaster could result in the loss of vital corporate assets or market share. To protect the organization and ensure the survival of the business, a comprehensive contingency plan is necessary. Some unique characteristics of the semiconductor industry are its equipment and its technological and capital‐intensive investments. As with any other industry, the uninterrupted provision of products and services to clients should be considered the key priority of the semiconductor industry. In this regard, this paper presents a systematic and proactive operational framework for the semiconductor industry to effectively anticipate, resist, and recover from disasters. The framework is composed of three phases: emergency response team, crisis management, and business continuity plan. The contents of these phases are discussed, and related workable procedures and measures are recommended to practitioners to ensure that organizations can continue to operate in the most adverse situations and thus remain viable and profitable during and after the crisis. Copyright © 2011 John Wiley & Sons, Ltd.     

公共危机下科普类公益海报的精准传达

公共危机在任何时候都是人类面临的巨大困扰,而危机时期的各种科普类公益海报的迅速传播,也一次又一次证明了其在应对危机的时候所显示出来的强大力量。随着社会进入到新时代,人们面临着反复出现的各种公共危机,传统的科普类型的公益海报也由原来的情感诉求逐渐转变成更为精准的信息传达。这也和当下人们所处的时代有关,公益海报的创意思路也就不仅仅只是局限在设计师的想象力。时代的进步,设计的力量也进一步印证了科学与艺术的结合所产生的强大创造力。本文的出发点就是从新时代、大数据、公益海报创作的方法、路径、创新等角度重新审视传统的公益海报创作,以期对科普类公益海报设计层面及其未来发展规律中找寻更多的可能性。     

Intelligent Feature Selection with Deep Learning Based Financial Risk Assessment Model

Due to global financial crisis, risk management has received significant attention to avoid loss and maximize profit in any business. Since the financial crisis prediction (FCP) process is mainly based on data driven decision making and intelligent models, artificial intelligence (AI) and machine learning (ML) models are widely utilized. This article introduces an intelligent feature selection with deep learning based financial risk assessment model (IFSDL-FRA). The proposed IFSDL-FRA technique aims to determine the financial crisis of a company or enterprise. In addition, the IFSDL-FRA technique involves the design of new water strider optimization algorithm based feature selection (WSOA-FS) manner to an optimum selection of feature subsets. Moreover, Deep Random Vector Functional Link network (DRVFLN) classification technique was applied to properly allot the class labels to the financial data. Furthermore, improved fruit fly optimization algorithm (IFFOA) based hyperparameter tuning process is carried out to optimally tune the hyperparameters of the DRVFLN model. For enhancing the better performance of the IFSDL-FRA technique, an extensive set of simulations are implemented on benchmark financial datasets and the obtained outcomes determine the betterment of IFSDL-FRA technique on the recent state of art approaches.     

企业危机生命周期管理

对企业危机、危机管理以及危机生命周期进行了阐述，提出了企业危机管理的PPRR模型，明确地说明了危机的生命周期管理过程，进行了企业危机管理小组机构设置以及职能划分，建立了危机预警系统及各阶段的预警子系统，阐述了企业危机各阶段管理的重要因素。     

基于粗神经网络的企业财务危机预警方法

分析了评价财务危机的指标体系和财务危机等级的划分,论述了粗神经网络的结构和基本原理,叙述了基于粗神经网络的财务危机预警方法,并给出了一个基于粗神经网络的财务危机的预警实例。实验结果表明,该方法应用于财务危机预警中是有效的,为财务危机预警提供了一条新的研究思路和方法。     

企业人力资源危机源传导的实证研究

通过相关文献研究和因素分析,提出企业内外部变化干扰因素是人力资源系统的间接危机源,人员内生性危机因子和企业制度性危机因子是人力资源系统的直接危机源.在此基础上,提出内外部变化干扰因素通过危机因子诱发人力资源危机的假设模型,同时提出了内外部变化干扰因素之间、人员内生性危机因子和企业制度性危机因子之间相互影响的研究假设.运用结构方程进行检验,在对检验结果分析的基础上探讨企业人力资源危机源的传导效应,从而为企业如何防范和控制人力资源危机的管理决策提供参考依据.     

外贸型物流企业供应链战略转型影响因素研究

提出了金融危机下外贸型物流企业向供应链战略转型的3个影响维度和10个影响因素。利用关联分析方法,建立了金融危机影响与外贸型物流企业供应链战略转型的4个关联模型,提出了一系列理论假设命题。通过东部沿海的5个地区企业的问卷采样,对假设与模型进行了实证研究,给出了金融危机影响与外贸型物流企业供应链战略转型的关联分析的路径系数图。结果表明,金融危机下外界环境变化、企业自身发展情况和问卷者的个人认识程度对供应链战略转型均有不同程度的正向影响,但资金流出现问题和收购兼并做大规模对供应链战略转型的必要性产生负向影响。     

Antecedents of technological readiness in times of crises: A comparison between before and during COVID-19

We examine how individual characteristics of employees such as digital self-efficacy, workforce agility, innovativeness, and commitment to change influence technological readiness in different stages of a crisis, i.e., before a crisis and during a crisis. We carried out a fuzzy set qualitative comparative analysis (fsQCA) on data from 2892 employees representing companies across several sectors and countries. Our results show that specific characteristics of employees can be beneficial for reaching technological readiness in organisations before a crisis and during a crisis. Our results, e.g., show that digital self-efficacy has a differential impact on technological readiness prior to a crisis and during a crisis while workforce agility is essential for both phases.     

China's Fumiture Industry——How to Deal with Foreign Teehnical Barriers to Trade in the Global Economic Crisis

At present,the global economic crisiscontinues to spread across the world.Theeconomies of all countries are sliding into aslump,trade protectionism is gaining ground,andexport orders have declined substantially for productprocessing and trading enterprises.Chinesefurniture companies are suffering from certainnegative impacts.China,as a large furniture producer,should draw lessons from this global economiccrisis.Furniture companies should enhancetheir capabilities of independent innovation andbrand build...     

COVID19: Forecasting Air Quality Index and Particulate Matter (PM2.5)

Urbanization affects the quality of the air, which has drastically degraded in the past decades. Air quality level is determined by measures of several air pollutant concentrations. To create awareness among people, an automation system that forecasts the quality is needed. The COVID-19 pandemic and the restrictions it has imposed on anthropogenic activities have resulted in a drop in air pollution in various cities in India. The overall air quality index (AQI) at any particular time is given as the maximum band for any pollutant. PM2.5 is a fine particulate matter of a size less than 2.5 micrometers, the inhalation of which causes adverse effects in people suffering from acute respiratory syndrome and other cardiovascular diseases. PM2.5 is a crucial factor in deciding the overall AQI. The proposed forecasting model is designed to predict the annual PM2.5 and AQI. The forecasting models are designed using Seasonal Autoregressive Integrated Moving Average and Facebook’s Prophet Library through optimal hyperparameters for better prediction. An AQI category classification model is also presented using classical machine learning techniques. The experimental results confirm the substantial improvement in air quality and greater reduction in PM2.5 due to the lockdown imposed during the COVID-19 crisis.