Attuning speech-enabled interfaces to user and context for inclusive design: technology, methodology and practice

This paper presents a methodology to apply speech technology for compensating sensory, motor, cognitive and affective usage difficulties. It distinguishes (1) an analysis of accessibility and technological issues for the identification of context-dependent user needs and corresponding opportunities to include speech in multimodal user interfaces, and (2) an iterative generate-and-test process to refine the interface prototype and its design rationale. Best practices show that such inclusion of speech technology, although still imperfect in itself, can enhance both the functional and affective information and communication technology-experiences of specific user groups, such as persons with reading difficulties, hearing-impaired, intellectually disabled, children and older adults.

产品情感交互设计探析

本文在对交互设计原则和方式的讨论中,引入了用户体验的概念。它能在人机交互中使用户获得人性的关怀,使人对产品产生情感,从而也为情感交互设计打下基础。     

“回收感动”——博物馆功能的再思考与博物馆信息交互平台之构想

博物馆因人的需要而设,也因人的发展而显得生机勃勃。博物馆的发展应该以展品为主到以观众为主,从"请勿触摸"到"欢迎参与"的转变。博物馆传播给观众的知识信息量越来越大,知识的传播不再是教育者向受教育者的单向传递,而是双向交流,互动影响。要在观众和博物馆之间建立一种联系,让观众参与到博物馆的展览中,从单方的接收信息到主动的去回收信息,创造一种新的服务方式,提供一种新的鉴赏体验,从而真正地满足观众的需求。     

浅谈卫浴产品造型设计与体验

本文以体验设计为出发点,从卫浴产品造型与用户体验论述了产品与生活形态的关联关系,指出在现代社会,设计师需要研究产品造型语言含义,创造人与卫浴产品之间一种更愉悦的使用体验。     

手机产品交互设计与用户体验探析

运用交互设计和用户体验的基本概念、产品交互系统组成图解、用户体验四元素,结合手机产品设计的用户调查和列表分析,获得了手机产品交互设计和用户体验的最终评价,通过这一比较和探析的过程证明,交互设计是未来设计尤其是工业产品设计的努力的方向和目标,用户体验是设计的终极参照。     

创造运动品牌店面独特的消费体验

在体验经济时代,消费者更渴望在选购服装时能获得一种美好而难忘的体验。基于此,本文提出联想式符号陈列法,主要研究运动品牌店面各区域陈列如何以运动场所或运动项目为灵感,营造出一种运动品牌特有的购物氛围,通过该陈列法的展示来引发消费者对产品的注意,以及感受到相应的运动场景,引起消费者共鸣,使消费者获得特殊的运动品牌符号信息和消费体验。     

设计艺术创造过程的研究

人类从远古走到今天,对设计艺术创造过程的认识一步步深入,随着社会经济、科技、文化的发展人们对设计艺术的创造也在不断的深化和完善。生活水平的提高使得人们对设计艺术也提出了更高的要求,本文就设计艺术创造过程的几个方面阐述自己的看法。从文中你可以觉察到设计艺术创造过程在我们设计艺术中的重要性。     

QoE enhancement of the industrial metaverse based on Mixed Reality application optimization

As a comprehensive integration of many new-generation information technologies, the metaverse has become a research hotspot that has attracted much attention. As a part of the metaverse, the industrial metaverse is expected to break through the constraints of space and time and promote high-quality industrial development. The industrial metaverse is human-centric, so its quality of experience (QoE) is a key topic. As one of the enabling technologies of the industrial metaverse, Mixed Reality (MR) can seamlessly integrate virtual information with the physical world and is widely regarded as an important window to the industrial metaverse. In close integration with other enabling technologies, industrial MR applications can be seen as a path toward the realization of the industrial metaverse; thus, the optimization of industrial MR applications can effectively achieve the QoE enhancement of the industrial metaverse. Based on the analysis of existing research and the characteristics of industrial scenarios, consistency, authenticity, smoothness, and comfort are identified as the factors that influence the user experience (UX) of industrial MR applications. Specific optimization methods for industrial MR applications are proposed to improve the UX with regard to these four factors. To verify the effectiveness of the proposed methods, a QoE evaluation model of the industrial metaverse based on the fuzzy analytic hierarchy process (FAHP) is established. Moreover, an industrial metaverse prototype for longwall mining that incorporates the proposed methods is developed and its QoE is evaluated. The results show that the proposed optimization methods for industrial MR applications significantly enhance the QoE in the industrial metaverse, and can provide better services for users in industrial systems, thus better serving these systems.     

Smart experience-oriented customer requirement analysis for smart product service system: A novel hesitant fuzzy linguistic cloud DEMATEL method

Smart product service system (PSS) has become an essential strategy to transform towards digital servitization for manufacturing companies. By leveraging smart capabilities, smart PSS aims to create superior user experience in a smart context. To develop a successful smart PSS, customer requirement management from smart experience perspective is necessary. However, it is a challenging task to identify and evaluate diverse, implicit and interrelated smart experience-oriented customer requirement (SEO-CR) in smart PSS context. Hence, this paper proposes an effective methodology to elicit and analyze SEO-CRs. At first, a generic, two-dimensional SEO-CR system is presented as a basis to derive the tailored SEO-CRs for various smart PSS applications. Second, a novel HFLC-DEMATEL (hesitant fuzzy linguistic cloud-based Decision-making and trial evaluation laboratory) method is proposed to accurately evaluate the priority and complicated interaction of SEO-CRs, considering the hesitancy, fuzziness and randomness under uncertain decision environment. Some new operations (e.g., cloud total-relation matrix and weight determination method) and a cloud influence relation map are developed to fully take advantage of cloud model in DEMATEL implementation. Finally, a real case of smart vehicle service system (SVSS) is presented. The 18 SEO-CRs of the SVSS are derived based on the generalized SEO-CRs. By using HFLC-DEMATEL, some important SEO-CRs in context of SVSS are identified, such as autonomous and convenience. The finding of results can help designers make proper decisions in design and development of SVSS with a superior smart experience. The effectiveness and reliability of the proposed method are validated by conducting some comparative analyses.     

Finite-time optimal tracking control for a class of nonlinear systems with prescribed performance

In this paper, a finite-time optimal tracking control scheme based on integral reinforcement learning is developed for partially unknown nonlinear systems. In order to realize the prescribed performance, the original system is transformed into an equivalent unconstrained system so as to a composite system is constructed. Subsequently, a modified nonlinear quadratic performance function containing the auxiliary tracking error is designed. Furthermore, the technique of experience replay is used to update the critic neural network, which eliminates the persistent of excitation condition in traditional optimal methods. By combining the prescribed performance control with the finite-time optimization control technique, the tracking error is driven to a desired performance in finite time. Consequently, it has been shown that all signals in the partially unknown nonlinear system are semiglobally practical finite-time stable by stability analysis. Finally, the provided comparative simulation results verify the effectiveness of the developed control scheme.