scholarly journals A User Biology Preference Prediction Model Based on the Perceptual Evaluations of Designers for Biologically Inspired Design

Symmetry ◽  
2020 ◽  
Vol 12 (11) ◽  
pp. 1860
Author(s):  
Shijian Luo ◽  
Yufei Zhang ◽  
Jie Zhang ◽  
Junheng Xu
Keyword(s):  
Prediction Model ◽  
Product Design ◽  
Linear Regression Analysis ◽  
User Preferences ◽  
User Preference ◽  
Biologically Inspired ◽  
Perceptual Evaluation ◽  
Biological Features ◽  
Cognitive Limitations ◽  
Biologically Inspired Design

Biology provides a rich and novel source of inspiration for product design. An increasing number of industrial designers are gaining inspiration from nature, producing creative products by extracting, classifying, and reconstructing biological features. However, the current process of gaining biological inspiration is still limited by the prior knowledge and experience of designers, so it is necessary to investigate the designer’s perception of biological features. Herein, we investigate designer perceptions of bionic object features based on Kansei engineering, achieving a highly comprehensive structured expression of biological features forming five dimensions—Overall Feeling, Ability and Trait, Color and Texture, Apparent Tactile Sensation, and Structural Features—using factor analysis. Further, producing creative design solutions with a biologically inspired design (BID) has a risk of failing to meet user preferences and market needs. A user preference prediction support tool may address this bottleneck. We examine user preference by questionnaire and explore its association with the perceptual evaluation of designers, obtaining a user preference prediction model by conducting multiple linear regression analysis. This provides a statistical model for identifying the relative weighting of the perception dimensions of each designer in the user preference for an animal, giving the degree of contribution to the user preference. The experiment results show that the dimension “Overall Feeling” of the designer perception is positively correlated with the “like” level of the user preference and negatively correlated with the “dislike” level of the user preference, indicating that this prediction model bridges the gap caused by the asymmetry between designers and users by matching the designer perception and user preference. To a certain extent, this research solves the problems associated with the cognitive limitations of designers and the differences between designers and users, facilitating the use of biological features in product design and thereby enhancing the market importance of BID schemes.

scholarly journals Perceived user preferences and usability evaluation of mainstream wearable devices for health monitoring

PeerJ ◽  
2018 ◽  
Vol 6 ◽  
pp. e5350 ◽  
Author(s):  
Yuxi Jia ◽  
Wei Wang ◽  
Dong Wen ◽  
Lizhong Liang ◽  
Li Gao ◽  
...  
Keyword(s):  
Product Design ◽  
Health Monitoring ◽  
Usability Evaluation ◽  
User Preferences ◽  
User Preference ◽  
Heart Health ◽  
Significant Difference ◽  
Health Related ◽  
Fitness Tracking ◽  
Fitness Trackers

Background There are many problems with fitness trackers, such as device usability, which limit their large-scale application, and relevant studies are limited in terms of their sample size and evaluation methods. The purpose of the study was to evaluate the perceived usability of various mainstream fitness trackers on the market, and to learn about user feedback on feature preferences for each device. Methods Trial use of seven mainstream fitness trackers (two smart watches and five smart wristbands) followed by a survey study were applied. The questionnaire was specifically developed for this study, which included two parts (user preferences and device usability in five dimensions). We recruited users to test the devices for at least 30 days and asked experienced users to provide feedback in order to evaluate each device, including the rating and user preference of each device. Results We received 388 valid questionnaires, in which users rated their responses on a five-point Likert scale. (1) User preference: the average user satisfaction was 3.50–3.86 (points), and the rating for willingness to buy averaged between 3.36 and 3.59. More users were willing to wear (58.3–81.3%) and purchase (56.8–83.0%) the devices than were not. The top three general feature preferences were daily activity tracking, heart health monitoring, and professional fitness tracking. The top three health-related feature preferences were heart rate monitoring, daily pedometer, and professional fitness tracking. (2) Usability evaluation: product design was rated from 3.57 to 4.00; durability, 3.63–4.26; ease of use, 3.70–3.90; added features, 3.30–3.83; and user-rated accuracy, 3.44–3.78. A significant difference was observed in the rating of product design and durability among the different devices (p < 0.05) score. Conclusions Users generally had positive subjective intent regarding fitness trackers but were less satisfied with their cost effectiveness. The users preferred health related features such as heart health monitoring, and professional fitness tracking. The rating of most of the current mainstream fitness trackers was fair with some significant differences among the devices. Thus, further improvement is needed.

Modeling and quantifying uncertainty in the product design phase for effects of user preference changes

2015 ◽  
Vol 115 (9) ◽  
pp. 1637-1665 ◽  
Author(s):  
Hamid Afshari ◽  
Qingjin Peng
Keyword(s):  
Life Cycle ◽  
Product Design ◽  
Product Life Cycle ◽  
User Preferences ◽  
User Preference ◽  
Design Parameters ◽  
Accurate Estimation ◽  
Product Life ◽  
Content Type ◽  
External Uncertainty

Purpose – The purpose of this paper is to quantify external and internal uncertainties in product design process. The research addresses the measure of product future changes. Design/methodology/approach – Two methods are proposed to model and quantify uncertainty in the product life cycle. Changes of user preferences are considered as the external uncertainty. Changes stemming from dependencies between components are addressed as the internal uncertainty. Both methods use developed mechanisms to capture and treat changes of user preferences. An agent-based model is developed to simulate sociotechnical events in the product life cycle for the external uncertainty. An innovative application of Big Data Analytics (BDA) is proposed to evaluate the external and internal uncertainties in product design. The methods can identify the most affected product components under uncertainty. Findings – The results show that the proposed method could identify product changes during its life cycle, particularly using the proposed BDA method. Practical implications – It is essential for manufacturers in the competitive market to know their product changes under uncertainty. Proposed methods have potential to optimize design parameters in complex environments. Originality/value – This research bridges the gap of literature in the accurate estimation of uncertainty. The research integrates the change prediction and change transferring, applies data management methods innovatively, and utilizes the proposed methods practically.

scholarly journals Predicting Implicit User Preferences with Multimodal Feature Fusion for Similar User Recommendation in Social Media

2021 ◽  
Vol 11 (3) ◽  
pp. 1064
Author(s):  
Jenq-Haur Wang ◽  
Yen-Tsang Wu ◽  
Long Wang
Keyword(s):  
Social Media ◽  
Feature Fusion ◽  
Relevant Information ◽  
Image Features ◽  
User Preferences ◽  
User Preference ◽  
Late Fusion ◽  
Multimodal Features ◽  
Fusion Methods ◽  
Text Features

In social networks, users can easily share information and express their opinions. Given the huge amount of data posted by many users, it is difficult to search for relevant information. In addition to individual posts, it would be useful if we can recommend groups of people with similar interests. Past studies on user preference learning focused on single-modal features such as review contents or demographic information of users. However, such information is usually not easy to obtain in most social media without explicit user feedback. In this paper, we propose a multimodal feature fusion approach to implicit user preference prediction which combines text and image features from user posts for recommending similar users in social media. First, we use the convolutional neural network (CNN) and TextCNN models to extract image and text features, respectively. Then, these features are combined using early and late fusion methods as a representation of user preferences. Lastly, a list of users with the most similar preferences are recommended. The experimental results on real-world Instagram data show that the best performance can be achieved when we apply late fusion of individual classification results for images and texts, with the best average top-k accuracy of 0.491. This validates the effectiveness of utilizing deep learning methods for fusing multimodal features to represent social user preferences. Further investigation is needed to verify the performance in different types of social media.

scholarly journals Biologically Inspired Design and Development of a Variable Stiffness Powered Ankle-Foot Prosthesis

2019 ◽  
Vol 11 (4) ◽  
Author(s):  
Alexander Agboola-Dobson ◽  
Guowu Wei ◽  
Lei Ren
Keyword(s):  
Lower Limb ◽  
Degrees Of Freedom ◽  
Sagittal Plane ◽  
Frontal Plane ◽  
Variable Stiffness ◽  
Plane Motion ◽  
Biologically Inspired ◽  
Passive Rotation ◽  
Ground Conditions ◽  
Biologically Inspired Design

Recent advancements in powered lower limb prostheses have appeased several difficulties faced by lower limb amputees by using a series-elastic actuator (SEA) to provide powered sagittal plane flexion. Unfortunately, these devices are currently unable to provide both powered sagittal plane flexion and two degrees of freedom (2-DOF) at the ankle, removing the ankle’s capacity to invert/evert, thus severely limiting terrain adaption capabilities and user comfort. The developed 2-DOF ankle system in this paper allows both powered flexion in the sagittal plane and passive rotation in the frontal plane; an SEA emulates the biomechanics of the gastrocnemius and Achilles tendon for flexion while a novel universal-joint system provides the 2-DOF. Several studies were undertaken to thoroughly characterize the capabilities of the device. Under both level- and sloped-ground conditions, ankle torque and kinematic data were obtained by using force-plates and a motion capture system. The device was found to be fully capable of providing powered sagittal plane motion and torque very close to that of a biological ankle while simultaneously being able to adapt to sloped terrain by undergoing frontal plane motion, thus providing 2-DOF at the ankle. These findings demonstrate that the device presented in this paper poses radical improvements to powered prosthetic ankle-foot device (PAFD) design.

scholarly journals Beyond analogy: A model of bioinspiration for creative design

2016 ◽  
Vol 30 (2) ◽  
pp. 159-170 ◽  
Author(s):  
Camila Freitas Salgueiredo ◽  
Armand Hatchuel
Keyword(s):  
Design Process ◽  
Design Theory ◽  
Leading Edge ◽  
Knowledge Bases ◽  
Biologically Inspired ◽  
Concept Knowledge ◽  
Bioinspired Design ◽  
Aerodynamic Properties ◽  
Biologically Inspired Design ◽  
The Impact

AbstractIs biologically inspired design only an analogical transfer from biology to engineering? Actually, nature does not always bring “hands-on” solutions that can be analogically applied in classic engineering. Then, what are the different operations that are involved in the bioinspiration process and what are the conditions allowing this process to produce a bioinspired design? In this paper, we model the whole design process in which bioinspiration is only one element. To build this model, we use a general design theory, concept–knowledge theory, because it allows one to capture analogy as well as all other knowledge changes that lead to the design of a bioinspired solution. We ground this model on well-described examples of biologically inspired designs available in the scientific literature. These examples include Flectofin®, a hingeless flapping mechanism conceived for façade shading, and WhalePower technology, the introduction of bumps on the leading edge of airfoils to improve aerodynamic properties. Our modeling disentangles the analogical aspects of the biologically inspired design process, and highlights the expansions occurring in both knowledge bases, scientific (nonbiological) and biological, as well as the impact of these expansions in the generation of new concepts (concept partitioning). This model also shows that bioinspired design requires a special form of collaboration between engineers and biologists. Contrasting with the classic one-way transfer between biology and engineering that is assumed in the literature, the concept–knowledge framework shows that these collaborations must be “mutually inspirational” because both biological and engineering knowledge expansions are needed to reach a novel solution.

Biologically Inspired Design: A Macrocognitive Account

2010 ◽  
Author(s):  
Swaroop S. Vattam ◽  
Michael Helms ◽  
Ashok K. Goel
Keyword(s):  
Biological Sciences ◽  
Information Processing ◽  
Engineering Design ◽  
Design Patterns ◽  
Information Processing Model ◽  
Biologically Inspired ◽  
Design Problems ◽  
Engineering Design Problems ◽  
Other Information ◽  
Biologically Inspired Design

Biologically inspired engineering design is an approach to design that espouses the adaptation of functions and mechanisms in biological sciences to solve engineering design problems. We have conducted an in situ study of designers engaged in biologically inspired design. Based on this study we develop here a macrocognitive information-processing model of biologically inspired design. We also compare and contrast the model with other information-processing models of analogical design such as TRIZ, case-based design, and design patterns.

Time-aware cloud manufacturing service selection using unknown QoS prediction and uncertain user preferences

2021 ◽  
pp. 1063293X2110195
Author(s):  
Ying Yu ◽  
Shan Li ◽  
Jing Ma
Keyword(s):  
Time Series Prediction ◽  
Service Selection ◽  
Cloud Manufacturing ◽  
Service Evaluation ◽  
User Preferences ◽  
User Preference ◽  
Selection Methods ◽  
Qos Prediction ◽  
Qos Performance ◽  
Time Aware

Selecting the most efficient from several functionally equivalent services remains an ongoing challenge. Most manufacturing service selection methods regard static quality of service (QoS) as a major competitiveness factor. However, adaptations are difficult to achieve when variable network environment has significant impact on QoS performance stabilization in complex task processes. Therefore, dynamic temporal QoS values rather than fixed values are gaining ground for service evaluation. User preferences play an important role when service demanders select personalized services, and this aspect has been poorly investigated for temporal QoS-aware cloud manufacturing (CMfg) service selection methods. Furthermore, it is impractical to acquire all temporal QoS values, which affects evaluation validity. Therefore, this paper proposes a time-aware CMfg service selection approach to address these issues. The proposed approach first develops an unknown-QoS prediction model by utilizing similarity features from temporal QoS values. The model considers QoS attributes and service candidates integrally, helping to predict multidimensional QoS values accurately and easily. Overall QoS is then evaluated using a proposed temporal QoS measuring algorithm which can self-adapt to user preferences. Specifically, we employ the temporal QoS conflict feature to overcome one-sided user preferences, which has been largely overlooked previously. Experimental results confirmed that the proposed approach outperformed classical time series prediction methods, and can also find better service by reducing user preference misjudgments.

scholarly journals Technical Characteristics in the Diffusion of Cleaner Residential Heating System in China: The Case of Air-Source Heat Pump Technology

2019 ◽  
Vol 12 ◽  
pp. 194008291985591 ◽  
Author(s):  
Dejin Su ◽  
Wenli Zhou ◽  
Qixia Du ◽  
Yongchun Huang
Keyword(s):  
Product Design ◽  
Heat Pump ◽  
User Satisfaction ◽  
Linear Regression Analysis ◽  
Heating System ◽  
Product Knowledge ◽  
Total Cost ◽  
Positive Effects ◽  
Air Source Heat Pump ◽  
Residential Heating

This study aims to explore the technical characteristics that affect user satisfaction with air-source heat pump technology which is recognized as one typical cleaner residential heating system and being promoted in China in response to the national “coal to electricity” policy. Moderated hierarchical linear regression analysis was conducted to analyze data from a questionnaire survey of 256 residents in suburban Beijing. Empirical results indicated that product convenience, product design, product reliability, product knowledge, and total cost, respectively, affect user satisfaction, but product safety has no significant effect on user satisfaction. Meanwhile, total cost is an important contingent factor that might weaken the positive effects of product convenience (or product design) on user satisfaction. Our research provides empirical evidence for identifying factors that influence user satisfaction with cleaner residential heating system in response to new energy policy and further provides useful managerial implications for market practice.

Biologically Inspired Design: Color on Wings

1997 ◽  
Vol 479 ◽  
Author(s):  
Mohan Srinivasarao ◽  
Luis Padilla
Keyword(s):  
Potassium Chlorate ◽  
Structural Variations ◽  
Biologically Inspired ◽  
Selective Reflection ◽  
Cholesteric Phase ◽  
Butterfly Wings ◽  
The Subject ◽  
Physical Effects ◽  
Biologically Inspired Design ◽  
Color Specification

Brilliant, iridescent colors found on the bodies and wings of many birds, butterflies and moths are produced by structural variations and have been the subject of study for centuries. Such brilliant colors have been described as metallic colors due to the saturation or purity of the color produced and have attracted the attention of great scientists like Newton, Michelson and Lord Rayleigh. It was recognized early on that such colors arise from physical effects such as interference or diffraction as opposed to colors that are normally produced due to the presence of chromophores which absorb or emit light. Common examples of physical colors are some butterfly wings [1], color of Indigo snake skin [2], hummingbird feathers [3,4], arthropod cuticles [which are due to selective reflection of color from the solidified cholesteric phase of chitin crystallites] [5], gemstones like opal [6,7], and some crystals like potassium chlorate [8]. While the origins of such colors are well understood the properties of color and color specification have not received much attention.

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