Natural Language Processing in-and-for Design Research

We review the scholarly contributions that utilise Natural Language Processing (NLP) methods to support the design process. Using a heuristic approach, we collected 223 articles published in 32 journals and within the period 1991-present. We present state-of-the-art NLP in-and-for design research by reviewing these articles according to the type of natural language text sources: internal reports, design concepts, discourse transcripts, technical publications, consumer opinions, and others. Upon summarizing and identifying the gaps in these contributions, we utilise an existing design innovation framework to identify the applications that are currently being supported by NLP. We then propose a few methodological and theoretical directions for future NLP in-and-for design research

KEER2022

Avanttítol: KEER2022. DiversitiesDescripció del recurs: 25 juliol 202

Perceived Quality of Cars. A Novel Framework and Evaluation Methodology.

The supremacy of the automotive manufacturers today is no longer driven by them achieving a superior manufacturing quality but increasingly depends on the customer’s quality perception. Average car consumers see a car’s quality as a fancy mixture of design, aesthetics, their own previous experiences and performance characteristics of the vehicle, unlike a combination of mechanical parts, software pieces, advanced materials, cutting-edge manufacturing processes, with technical knowledge, skills and high production volumes – all ingredients involved in the modern car creation. Perceived quality is one of the most critical aspects for product development that defines successful car design.Speaking of perceived quality, we are dealing with a complex, multifaceted adaptive system; a system where a human is the main agent. “Which product characteristics require the most attention for successful car design?”\ua0 This is the question engineers and designers need to answer under the pressure of shrinking product development time, available technologies, and financial limitations, not to mention that the answer is expected to be given in numbers to sustain the fierce competition in today’s automotive industry. For this reason, the perceived quality must be understood and controlled during all stages of product development. The research presented in this thesis justifies the engineering viewpoint on perceived quality as an inevitable part of new product development. The core of this research is the Perceived Quality Framework (PQF), a taxonomy structure of perceived quality attributes and the Perceived Quality Attributes Importance Ranking (PQAIR) method, a novel method for perceived quality evaluation that can be applied to a variety of products, including cars. The PQF communicates the attribute-centric engineering viewpoint on quality perception, developed through cumulative studies in the premium and luxury market segment of the automotive industry. The PQAIR method equips engineers with practical tools for perceived quality evaluation. The proposed method helps to reach the equilibrium of the product’s quality equation from the perspective of design effort, time, and costs estimations.Altogether this introduces a new paradigm of perceived quality as the inevitable element integrated into the process of engineering endeavor regarding product attributes that communicates quality to the customer

Link Prediction with Deep Learning Models

Deep Learning has been used extensively in many applications by researchers. With the increased attraction to Deep Learning, more and more unique models are created each year. However, sometimes some of the model details are not included in the publications. This makes using new Deep Learning models for research a time-consuming task for researchers. In order to tackle with this problem, we propose a prediction mechanism for the missing information in the model. By creating a dataset where the Deep Learning models are represented as knowledge graphs, we made it possible to use knowledge graph embedding algorithms which are specifically designed for eliminating missing information in a given data. We inspected 6 different algorithms and compared their performances on a small-scale experiment. After the comparison, we picked the most promising algorithm and used it for link prediction in Deep Learning models

Effect of surface roughness on quality perception of Laser Sintered (LS) parts

Additive Manufacturing (AM) is a revolutionary technology that in recent years has become increasingly visible in mainstream media and is in the process of being developed for more widespread industrial applications. One of the challenges that has hindered the growth of AM in industry has been the aspect of surface finish, particularly in the use of Laser Sintering (LS). The surfaces produced are often perceived to be of a lower quality than those of other more traditional techniques. One of the ways in which developments have been made to address this issue is to use different post-processing techniques to achieve a variety of surface finishes. These decisions are often made by the machine manufacturers and researchers without any input from the product consumers. This thesis aims to include the consumer in the surface finish decision-making process. The main focus is to investigate the consumer perceptions of different LS surface finishes and roughness through the utilization and adaptation of human interaction and social science techniques. A group of 44 participants performed a number of blind trials on different roughness parts. It was found that up to a certain point a decrease in roughness led to a growth in perceived quality, but this increase was not infinite. All users identified roughness and smoothness as directly relating to quality; whilst other vocabulary was used to describe quality, these did not translate to “real” effects during testing. Crucially 50% of participants’ opinions of quality changed when allowed to perform a visual assessment of the parts

Improving Recall of Browsing Sets in Image Retrieval from a Semiotics Perspective

The purpose of dissertation is to utilize connotative messages for enhancing image retrieval and browsing. By adopting semiotics as a theoretical tool, this study explores problems of image retrieval and proposes an image retrieval model. The semiotics approach conceptually demonstrates that: 1) a fundamental reason for the dissonance between retrieved images and user needs is representation of connotative messages, and 2) the image retrieval model which makes use of denotative index terms is able to facilitate users to browse connotatively related images effectively even when the users' needs are potentially expressed in the form of denotative query. Two experiments are performed for verifying the semiotic-based image retrieval model and evaluating the effectiveness of the model. As data sources, 5,199 records are collected from Artefacts Canada: Humanities by Canadian Heritage Information Network, and the candidate terms of connotation and denotation are extracted from Art & Architecture Thesaurus. The first experiment, by applying term association measures, verifies that the connotative messages of an image can be derived from denotative messages of the image. The second experiment reveals that the association thesaurus which is constructed based on the associations between connotation and denotation facilitates assigning connotative terms to image documents. In addition, the result of relevant judgments presents that the association thesaurus improves the relative recall of retrieved image documents as well as the relative recall of browsing sets. This study concludes that the association thesaurus indicating associations between connotation and denotation is able to improve the accessibility of the connotative messages. The results of the study are hoped to contribute to the conceptual knowledge of image retrieval by providing understandings of connotative messages within an image and to the practical design of image retrieval system by proposing an association thesaurus which can supplement the limitations of the current content-based image retrieval systems (CBIR)

Effect of surface roughness on quality perception of Laser Sintered (LS) parts

Additive Manufacturing (AM) is a revolutionary technology that in recent years has become increasingly visible in mainstream media and is in the process of being developed for more widespread industrial applications. One of the challenges that has hindered the growth of AM in industry has been the aspect of surface finish, particularly in the use of Laser Sintering (LS). The surfaces produced are often perceived to be of a lower quality than those of other more traditional techniques. One of the ways in which developments have been made to address this issue is to use different post-processing techniques to achieve a variety of surface finishes. These decisions are often made by the machine manufacturers and researchers without any input from the product consumers. This thesis aims to include the consumer in the surface finish decision-making process. The main focus is to investigate the consumer perceptions of different LS surface finishes and roughness through the utilization and adaptation of human interaction and social science techniques. A group of 44 participants performed a number of blind trials on different roughness parts. It was found that up to a certain point a decrease in roughness led to a growth in perceived quality, but this increase was not infinite. All users identified roughness and smoothness as directly relating to quality; whilst other vocabulary was used to describe quality, these did not translate to “real” effects during testing. Crucially 50% of participants’ opinions of quality changed when allowed to perform a visual assessment of the parts

A Review on Human-Computer Interaction and Intelligent Robots

In the field of artificial intelligence, human–computer interaction (HCI) technology and its related intelligent robot technologies are essential and interesting contents of research. From the perspective of software algorithm and hardware system, these above-mentioned technologies study and try to build a natural HCI environment. The purpose of this research is to provide an overview of HCI and intelligent robots. This research highlights the existing technologies of listening, speaking, reading, writing, and other senses, which are widely used in human interaction. Based on these same technologies, this research introduces some intelligent robot systems and platforms. This paper also forecasts some vital challenges of researching HCI and intelligent robots. The authors hope that this work will help researchers in the field to acquire the necessary information and technologies to further conduct more advanced research

Enterprise Business Alignment Using Quality Function Deployment, Multivariate Data Analysis And Business Modeling Tools

This dissertation proposes two novel ideas to enhance the business strategy alignment to customer needs. The proposed business alignment clock is a new illustration to the relationships between customer requirements, business strategies, capabilities and processes. To line up the clock and reach the needed alignment for the enterprise, a proposed clock mechanism is introduced. The mechanism integrates the Enterprise Business Architecture (EBA) with the House of Quality (HoQ). The relationship matrix inside the body of the house is defined using multivariate data analysis techniques to accurately measure the strength of the relationships rather than defining them subjectively. A statistical tool, multivariate data analysis, can be used to overcome the ambiguity in quantifying the relationships in the house of quality matrix. The framework is proposed in the basic conceptual model context of the EBA showing different levels of the enterprise architecture; the goals, the capabilities and the value stream architecture components. In the proposed framework, the goals and the capabilities are inputs to two houses of quality, in which the alignment between customer needs and business goals, and the alignment between business goals and capabilities are checked in the first house and the second house, respectively. The alignment between the business capabilities and the architecture components (workflows, events and environment) is checked in a third HoQ using the performance indicators of the value stream architecture components, which may result in infrastructure expansion, software development or process improvement to reach the needed alignment by the enterprise. The value of the model was demonstrated using the Accreditation Board of Engineering and Technology (ABET) process at the Industrial Engineering and Management Systems department at the University of Central Florida. The assessment of ABET criteria involves an evaluation of the extent to which the program outcomes are being achieved and results in decisions and actions to improve the Industrial Engineering program at the University of Central Florida. The proposed framework increases the accuracy of measuring the extent to which the program learning outcomes have been achieved at the department. The process of continuous alignment between the educational objectives and customer needs becomes more vital by the rapid change of customer requirements that are obtained from both internal and external constituents (students, faculty, alumni, and employers in the first place)

Robotics 2010

Without a doubt, robotics has made an incredible progress over the last decades. The vision of developing, designing and creating technical systems that help humans to achieve hard and complex tasks, has intelligently led to an incredible variety of solutions. There are barely technical fields that could exhibit more interdisciplinary interconnections like robotics. This fact is generated by highly complex challenges imposed by robotic systems, especially the requirement on intelligent and autonomous operation. This book tries to give an insight into the evolutionary process that takes place in robotics. It provides articles covering a wide range of this exciting area. The progress of technical challenges and concepts may illuminate the relationship between developments that seem to be completely different at first sight. The robotics remains an exciting scientific and engineering field. The community looks optimistically ahead and also looks forward for the future challenges and new development