Using Personas to Support Augmentative Alternative Communication Device Design: A Validation and Evaluation Study

Interactive computing devices are increasingly being deployed to support individuals in improving and managing health, aging in place, and as assistive devices for those with functional limitations. Augmentative Alternative Communication (AAC) aids are devices that help individuals with speech impairments communicate. They are typically prescribed by clinicians (speech–language pathologists) based on a specific individual’s physical needs and disease classification. While personas have been used in the design of other consumer technologies, they have not been frequently deployed in the design of clinically oriented technologies, including AAC devices. Instead, a clinical/rehabilitation engineering approach to AAC design is typically used, focusing on the physical and symptomatic needs of a diverse group of individuals, and involving the consumer on the level of making feature recommendations and/or testing the technology near the end of the design and production process. To address this challenge, three personas of individuals with amyotrophic lateral sclerosis were developed, intended for use in AAC device design. This article presents results from two studies which evaluated the personas. In the first study, personas were validated using an online survey of eight speech–language pathologists, and interviews of seven individuals with ALS that were not involved in the development of personas. In the second study, AAC device designers were asked to assess the potential utility of the personas for AAC device design. Results showed that developed personas had validity in representing individuals with ALS and that the personas would be useful for AAC device designers. The methods used can be extended for validation and assessment of personas developed for other purposes.     

Metrics for evaluating human information interaction systems

Society today has a wealth of information available due to information technology. The challenge facing researchers working in information access is how to help users easily locate the information needed. Evaluation methodologies and metrics are important tools to assess progress in human information interaction (HII). To properly evaluate these systems, evaluations need to consider the performance of the various components, the usability of the system, and the impact of the system on the end user. Current usability metrics are adequate for evaluating the efficiency, effectiveness, and user satisfaction of such systems. Performance measures for new intelligent technologies will have to be developed. Regardless of how well the systems are and how usable the systems are, it is critical that impact measures are developed. For HII systems to be useful, we need to assess how well information analysts work with the systems. This evaluation needs to go beyond technical performance metrics and usability metrics. What are the metrics for evaluating utility? This paper describes research efforts focused on developing metrics for the intelligence community that measure the impact of new software to facilitate information interaction.     

Intuitionistic fuzzy PRI-AND and PRI-OR aggregation operators

In this paper, we investigate the multi-attribute decision making (MADM) problem under Atanassov’s intuitionistic fuzzy environment in which the attributes are in different priority levels. We develop the intuitionistic fuzzy prioritized “and” operator and intuitionistic fuzzy prioritized “or” operator, which are motivated by the idea of Yager’s prioritized “and” operator and prioritized “or” operator. These intuitionistic fuzzy prioritized aggregation operators can be applied to aggregate intuitionistic fuzzy information when the attributes are in different priority levels. A practical example is used to illustrate the applicability and effectiveness of the proposed intuitionistic fuzzy prioritized “or” operator.     

浅谈现代工业产品设计的趋势转变

本文从近年来人们情感需求、生活方式、设计手段等方面的变化出发,探讨了现代工业产品设计的几种转变趋势,分析并阐述为从功能设计到情感设计的转变;从技术设计到理念设计的转变;从单体设计到系统设计的转变;从整体设计到细节设计的转变等方面,进一步开拓设计师的设计思路。     

A Problem-based Selection of Multi-attribute Decision-making Methods

Different multi-attribute decision-making (MADM) methods often produce different outcomes for selecting or ranking a set of decision alternatives involving multiple attributes. This paper presents a new approach to the selection of compensatory MADM methods for a specific cardinal ranking problem via sensitivity analysis of attribute weights. In line with the context-dependent concept of informational importance, the approach examines the consistency degree between the relative degree of sensitivity of individual attributes using an MADM method and the relative degree of influence of the corresponding attributes indicated by Shannon's entropy concept. The approach favors the method that has the highest consistency degree as it best reflects the decision information embedded in the problem data set. An empirical study of a scholarship student selection problem is used to illustrate how the approach can validate the ranking outcome produced by different MADM methods. The empirical study shows that different problem data sets may result in a different method being selected. This approach is particularly applicable to large-scale cardinal ranking problems where the ranking outcome of different methods differs significantly.     

An intelligent decision theoretic approach to producibility optimization in conceptual design

Product optimization involves selecting design, manufacturing, and support attributes that can produce the best system. Producibility or manufacturability is the term often used to describe the relative ease of manufacturing a product. In complex systems, productibility optimization is a very difficult process, particularly when the values of many attributes are restricted by constraints. One challenge is to develop more universal producibility metrics for the conceptual design phase when design information is limited and drawings are nondimensional. This paper develops a new method for producibility optimization in conceptual design based on a combination of both decision theoretic and expert system techniques. Decision theoretic techniques provide the means to model the design for producibility problem in a manner that can deal with risk, uncertainty, and user (or corporate) preferences, and can effectively integrate diverse factors to provide a measure of the overall worth of a design. The particular decision theoretic approach employed is based on multi-attribute utility theory. An illustrative example of the methodology is applied to the conceptual design of a structural composite part.     

Neutrosophic structured element

This paper presents a new concept in neutrosophic sets (NS) called neutrosophic structured element (NSE). Based on this concept, we define the operational laws, score function, and some aggregation operators of NS. Finally, as an application of this concept, we propose a decision-making method for a multi-attribute decision making (MADM) problem under NSE information. The results indicate that this concept is a useful tool for dealing with neutrosophic decision problems.     

基于信息测度的勾股模糊决策模型及其应用

相对于直觉模糊集，勾股模糊集能够更为全面和有效地表达描述复杂问题中的不确定和非一致信息，使其受到了广泛研究。对于属性评价值为勾股模糊数并且属性指标权重信息数据完全未知的多属性决策问题，以提出的勾股模糊信息测度为基础，设计了新的多属性决策模型。该模型运用对数函数设计了一种新的勾股模糊数信息熵计算方法；引入了勾股模糊相似度概念，并结合对数行数提出勾股模糊数相似度的衡量方法，随后挖掘出勾股模糊数的信息熵和相似度之间的内在联系；运用提出的勾股模糊熵和相似度计算方法，构建新的多属性决策模型，并进行应用研究。实验结果表明，提出的模型合理有效，同时拓展了模型的使用范围。     

Cyber-physical systems alter automation architectures

Recent automation systems are well structured according to tasks fulfilled by the functions executed on dedicated devices. These functional assignments are also reasons for the design and topology of fieldbus communication systems. New approaches like Cyber Physical System (CPS) require different approaches according to existing communication technologies and engineering. On one side the interaction models advance, and on the other side the demands for industrial plants become a lot more flexible. This article shows upcoming demands on automation systems and discusses new strategies for software deployment of automation applications and communication systems to fulfill these requirements. This includes handling of different types of functional coupling, e.g. loose coupling with internet/web based technologies for interaction and information management. In addition the current device models offering specific device functions have to be adapted to the new CPS approach.     

考虑心理行为的区间二元语义动态群决策方法

针对当前属性值为区间语言信息的群决策方法的不足,提出了一种考虑决策者心理行为的区间二元语义动态多属性群决策方法。定义了一种更接近决策者思维习惯的区间二元语义新的距离公式;引入时间度概念,结合考虑专家评价的综合一致性,建立优化模型求解时序权重;并基于前景理论,构建前景偏差值最小化的权重优化模型;采用基于新距离测度的交互式多属性决策（TODIM）方法计算方案的综合总体优势度,以此对方案进行排序。并以供应链协同合作伙伴的选择与评价为例,验证了所提方法的有效性和合理性。     

Using information systems to improve energy efficiency: Do smart meters make a difference?

The large-scale generation of electricity is a major contributor to increasing levels of greenhouse gas emissions, putting pressure on the industry to reduce its environmental impacts. Electricity utility companies are looking to two strategies to help make this happen: the smart grid and demand-side management. Viewing the challenge from an IS perspective, this study attempts to answer the question: do smart grid information systems and technologies make a difference in utilities’ efforts to promote energy efficiency? Drawing on organizational information processing theory and extending it by integrating the concept of information waste, two competing hypotheses are developed and tested using hierarchical regression and data from 543 U.S. electricity utilities. The model, incorporating four levels of metering devices, is found to explain a high portion of the variance in energy efficiency effects of demand-side management programs. This suggests that there are IS-enabled information processing capacities within smart meters that have a significant influence on utilities’ EDM effectiveness. However, the results also point to the potential for both positive and negative effects. Implications of these findings for practice and future research directions are discussed.     

产品概念设计可制造性评价方法研究

随着新产品开发技术的发展,人们对产品使用性能和外观艺术的要求越来越高。但概念设计不仅仅体现艺术性,更应符合工业产品的制造特点和使用特性。认为产品概念设计方案的可制造性决定于概念设计的工业设计阶段,并针对工业设计因素建立概念设计评价体系。认为产品概念设计可制造性评价是一个多层次、多属性的决策问题,建立概念设计评价模型,并基于多属性决策的理论知识给予了解决。     

Integrative development of product and production system for mechatronic products

The increasing penetration of mechanical engineering by information technology enables considerable benefits. The arising new discipline is referred to by the term mechatronics, which expresses the close integration of mechanics, electrics/electronics, control engineering and software engineering. Hence, the design and production of such systems is an interdisciplinary and complex task. An effective and continuous cooperation and communication between developers from different domains during the whole development process is required. Moreover, the multidisciplinary and synergetic effectiveness of mechatronic systems as well as new production technologies cause strong interdependencies between system parts, which are to be produced. As a consequence, the production system determines the product concept. Restrictions by manufacturing technologies have to be considered already during the early stages of the product development. This contribution deals with the stated problem by providing both, a generic procedure model and a specification technique for the integrative development of mechatronic products and their production systems.     

Common design structures and substitutable feature discovery in CAD databases

It has been widely reported that the reuse of previously created components, or features, in new engineering designs will improve the efficiency of a company’s product development process. Although the reuse of engineering components has established metrics and methodologies, the reuse of specific design features (e.g. stiffening ribs, hole patterns or lubrication grooves, etc.) has received less attention in the literature. Typically, researchers have reported approaches to partial design reuse that identify patterns predominately in terms of geometrically similar shapes (i.e. a set of features) whose elements are adjacent, cohesive, and decoupled from the overall form of a component.In contrast, this paper defines a common design structure (CDS) as collections of frequently occurring features (e.g. holes) with common parametric values (e.g. diameters) in a CAD database (irrespective of their locations or spatial connectivity between other features on a component). By exploiting the established data-mining technology of association rules and item-sets the authors show how CDSs can be efficiently computed for hundreds of 3D CAD models. A case study, with hole data extracted from a publicly available dataset of hydraulic valves, is presented to illustrate how item-sets associated with CDS can be computed and used to support predictive design by identifying potentially ‘substitutable features’ during an interactive design process. This is done using a combination of association rules and geometric compatibility checks to ensure the system’s suggestion are implementable. The use of the Kullback–Leibler divergence to assess the degree of similarity between components is identified as a crucial step in the process of identifying the “best” suggestions. The results illustrate how the prototype implementation successfully mines the CDSs and identifies substitutable hole features in a dataset of industrial valve designs.     

A general U-block model-based design procedure for nonlinear polynomial control systems

The proposition of U-model concept (in terms of ‘providing concise and applicable solutions for complex problems’) and a corresponding basic U-control design algorithm was originated in the first author's PhD thesis. The term of U-model appeared (not rigorously defined) for the first time in the first author's other journal paper, which established a framework for using linear polynomial control system design approaches to design nonlinear polynomial control systems (in brief, linear polynomial approaches → nonlinear polynomial plants). This paper represents the next milestone work – using linear state-space approaches to design nonlinear polynomial control systems (in brief, linear state-space approaches → nonlinear polynomial plants). The overall aim of the study is to establish a framework, defined as the U-block model, which provides a generic prototype for using linear state-space-based approaches to design the control systems with smooth nonlinear plants/processes described by polynomial models. For analysing the feasibility and effectiveness, sliding mode control design approach is selected as an exemplary case study. Numerical simulation studies provide a user-friendly step-by-step procedure for the readers/users with interest in their ad hoc applications. In formality, this is the first paper to present the U-model-oriented control system design in a formal way and to study the associated properties and theorems. The previous publications, in the main, have been algorithm-based studies and simulation demonstrations. In some sense, this paper can be treated as a landmark for the U-model-based research from intuitive/heuristic stage to rigour/formal/comprehensive studies.     

杭州湖滨国际名品街公共设施设计探究

公共设施是现代化城市的组成部分,协调着人与城市环境的关系。如何才能创造出符合现代生活需求的公共设施,设计原则至关重要。本文从安全性、功能性、人性化、环境协调性、系统性等五个方面阐述了公共设施的设计原则。本文首先结合湖滨路的特点的研究,来阐述富有创新设计的公共设施在湖滨路上的体现,在设计上应该突破传统的"城市街道摆设"概念,来进一步说明我们所设计的公共设施如何利用的。做到以人为本,使人们的生活更加便捷、高效。     

产品工业设计可制造性评价方法研究

针对传统的产品工业设计流程存在的效率低、资源浪费、可制造性评价方法单一且客观性差等问题,设计并构建了一个融合工业设计属性内容的可制造性评价方法,并且给出了方法的具体结构及实施步骤。结合一种基于依赖型不确定语言有序加权几何（Dependent Uncertain Linguistic Ordered Weighted Geometric,DULOWG）算子的多属性群决策方法,建立工业设计可制造性评价模型,并基于多属性决策的理论知识进行了推理和验证。     

A method for discrete stochastic MADM problems based on the ideal and nadir solutions

Many real life decision making problems can be modeled as discrete stochastic multi-attribute decision making (MADM) problems. A novel method for discrete stochastic MADM problems is developed based on the ideal and nadir solutions as in the classical TOPSIS method. In a stochastic MADM problem, the evaluations of the alternatives with respect to the different attributes are represented by discrete stochastic variables. According to stochastic dominance rules, the probability distributions of the ideal and nadir variates, both are discrete stochastic variables, are defined and determined for a set of discrete stochastic variables. A metric is proposed to measure the distance between two discrete stochastic variables. The ideal solution is a vector of ideal variates and the nadir solution is a vector of nadir variates for the multiple attributes. As in the classical TOPSIS method, the relative closeness of an alternative is determined by its distances from the ideal and nadir solutions. The rankings of the alternatives are determined using the relative closeness. Examples are presented to illustrate the effectiveness of the proposed method. Through the examples, several significant advantages of the proposed method over some existing methods are discussed.     

Sensor placement for robust burst identification in water systems: Balancing modeling accuracy,parsimony, and uncertainties

Urban water systems are seeing an uptake in using advanced sensing technology. Incorporating sensors for monitoring water distribution systems (WDSs) provides promising benefits to water utilities by enabling a shift from reactive to proactive pipe failure detection and from delayed water loss management to automatic sense-and-respond capabilities. Despite the opportunities that new sensing technologies create, a budget-constrained utility is challenged with identifying sensing locations in the WDS that will maximize information gain. To address this gap, this paper studies the problem of optimal placement of high-frequency pressure sensors in WDSs for pipe burst identification. This paper proposes a sensor placement strategy to address the challenges of data and modeling uncertainty by incorporating robust representation and tolerance analysis into an optimization framework with the objective of achieving the best detection and identification of burst events. Transient simulations are first used to predict system’s response to burst events, demonstrating the importance of modeling accuracy over approximation methods. A robust event representation approach is then presented to summarize system response to pipe bursts using signature matrices. Subsequently, the identification problem is cast as a minimum test cover problem when the number of available sensors is unlimited, and as the maximum covering test problem when the number of available sensors is limited. The optimization problems are then formulated and solved using mixed integer linear programming. Four complementary metrics are suggested to evaluate the performance of the sensor placement designs. Multiple criteria decision analysis is then applied to select the placement design while balancing information gain and cost. The results show that incorporating more information can improve event identification, but sufficient accuracy of the extracted information is required to accrue the benefits.     

Towards a suite of quality metrics for KADS-domain knowledge

In this paper, the quality metrics suite for object oriented (OO) design is partially used as an initial concept to develop metrics for statically measuring quality of KADS-domain knowledge bases. KADS-domain knowledge bases have common characteristics with OO, and other distinct features that limit the usage of some OO quality metrics. Therefore, new sets of domain knowledge quality metrics are proposed. The proposed matrices are enriched with an automatic tool used to measure quality of real world expert systems. In order to assess the effectiveness of these proposed quality metrics, these metrics were applied on a sample of real world agriculture application domains developed by CLAES (The Central Laboratory of Agriculture Expert System). Finally, complete analysis of the results obtained due to applying these metrics is presented.