Preferred Design Research Articles

The effects of icon design features on user perception and preference: A case study of icons for Covid-19.

The objective of this study is to evaluate users' perceptions and preferences on the design features of the COVID-19 prevention promotion icon from the perspective of users' aesthetic and perceptual needs. In this study, 120 officially published icons from 24 countries and regions were collected from online platforms for ranking tests, and then the top-ranked icons were subjectively rated by the semantic differential method. By evaluating the quality of users' perceptions of multiple semantic dimensions of icons, we extracted the perceptual semantic words that users valued as the main icon design features. Spearmen correlations were applied to derive possible correlations between user rankings and semantic scales, and a Friedman test was also conducted to determine the true differences in user perceptions and preferences for different styles of icons. Factor analysis was conducted to extract six perceptual words that influence the design features of the COVID-19 prevention promotion icon. The methodology adopted in this study facilitated the screening of design features related to icon effectiveness, and the findings show that "Interesting," "Simple," "Familiar, "Recognizable," "Concrete," and "Close(semantic distance)" are the key features that influence users' perception and preference of COVID-19 icon design. The results of this study can be used as the basis for designing and improving publicity icons for preventive measures in COVID-19, and the methods adopted in this study can be applied to evaluate other types of icon design.

Acanthus ornament generation using layout subdivisions with parameterized motifs

AbstractAcanthus ornaments frequently adorn Western architectural designs. The placement of these motifs varies according to the decorative object, with some having motifs arranged in a grid pattern. In this study, we propose a procedural modeling system aimed at generating acanthus ornaments on a planar surface. The proposed approach initially establishes the layout of boundary grids for acanthus motifs by subdividing the target surface into nonuniform grids. Subsequently, the medial axis line of the acanthus motif is generated to optimally conform to each boundary grid, employing a parameterized representation of deformable motifs. The three‐dimensional motif shapes are ultimately constructed from the medial axis, with the shape parameters adjusted to improve aesthetic appeal. The proposed system generates various acanthus ornaments through rule‐based layout subdivisions, offering users the option to select their preferred design while adjusting the motif shapes with a few manual parameters.

Exploring the impact of landscape design on user preferences in shopping centers post the COVID-19 Pandemic

This study explores the impact of landscape design, which has gained importance alongside architectural changes in shopping centers, and investigates preferences in the post-COVID-19 pandemic era. Although e-commerce has increased during the pandemic, research and societal behaviors suggest that shopping centers will continue to serve as contemporary agoras due to their socialization and leisure functions. However, in response to the pandemic, it is anticipated that newly designed shopping centers will be architecturally conceived as semi-outdoor or outdoor spaces, regardless of climate conditions. This transformation will involve the softening of rigid appearances through landscape elements, making them both ecologically and psychologically sustainable. The number of studies on this subject is limited. To address this knowledge gap, an online survey was conducted with 586 randomly selected users across nine shopping centers located in three major cities of Turkey: Istanbul, Ankara, and Izmir, with three shopping centers in each city. The survey investigated users' preferences for architectural styles (indoor, semi-outdoor, or outdoor) and landscape design in shopping centers. The findings of the study indicate that post-pandemic, outdoor and semi-outdoor shopping centers are likely to be preferred more frequently. An emphasis is likely to be placed on natural landscape elements such as plants and water features in landscape design. Furthermore, shopping center designs are likely to become simpler, offering comfortable and spacious navigation areas while optimizing parking and transportation conditions. This study is expected to shed light on decision-making processes for future shopping centers. By incorporating consumer preferences, architects can enhance the sustainability of shopping center investments through next-generation design.

Systematic design of tree-like branching network microchannel heat sinks for enhanced heat transfer with nanofluids

Branched or tree-shaped networks of microchannels are often preferred heatsink designs for microelectronic cooling due to their ability to offer a substantially large surface area-to-volume ratio. Designing an optimized tree-shaped heatsink in terms of hydrothermal performance poses challenges due to the intricate geometry and small-scale fluid–structure interactions involved, making prototyping challenging. We propose a systematically designed microchannel network heat exchanger inspired by tree branching patterns, aiming for ease in rapid prototyping and improved flow distributions offering enhanced thermal performance. Starting from a simpler geometrical consideration, we systematically improve the design by introducing a pin fin at the junction for improved flow distribution and then by imparting a converging angle in the channel for enhanced thermal performance. Additionally, we conduct an entropy generation analysis to examine the thermal performance of various nanofluid concentrations within the proposed device and witness significant thermal performance improvement that can benefit the thermal management of microelectronic components and other cooling applications.

A COMPARATIVE STUDY ON BIOPHILIC PREFERENCES OF SCHOOL LEARNING SETTINGS: A CASE OF ELEMENTARY SCHOOLS IN ASIA

Countless studies have demonstrated evidence of the significance of nature in learning settings on children's performance globally. Children exposed to a learning setting based on nature tend to perform better than those in a typical classroom. Studies have also found that the current generation obtains indirect nature experiences through various e-learning platforms rather than experiencing nature directly in modern society. Recent studies found that an inconducive school design environment that does not fully support students’ needs and preferences is one of the main reasons for this. Hence, this paper explores children’s choices for biophilic elements in primary school design in three Asian countries: Malaysia, Indonesia, and Thailand. The online survey questionnaire was used as a qualitative method to collect the stipulated data. The results revealed that biophilic elements are highly favourable to the students from all three countries except for the different elements they preferred. In particular, the results found that planting elements within the school area are the biophilic element most preferred by students in Indonesia and Thailand. Meanwhile, students in Malaysia prefer animals (pets and birds). The data and results presented in the present study can be used as a general guideline, particularly in integrating nature as part of the future school design elements in Asian countries. Note that each design preference shows a different result based on each school’s preferences in the three countries.

A new product development method to incorporating customer sensory preferences in food product design

As the way people consume has changed, the focus of customer satisfaction has moved away from engineering and towards sensory preferences (SPs), necessitating a new approach to product development. This paper introduces a novel product development model that incorporates SP factors. First, utilizing literature and expert input, a domain-specific food sensory attribute knowledge graph is built. Then, SPs/non-sensory preferences (NSPs) are extracted from extensive online product evaluations using Latent Dirichlet allocation (LDA) and sentiment analysis. Customer preferences (CPs) are formed by combining quantifiable SPs/NSPs. Following that, CPs are used to design and distribute product components. To improve customer satisfaction, a new product development approach has been developed. Finally, a genetic algorithm is applied to the optimization model in order to determine the best product development approach. This model has been empirically and comparatively demonstrated to be practical and effective.

Wearable devices for out-of-hospital cardiac arrest: A population survey on the willingness to adhere.

When an out-of-hospital cardiac arrest (OHCA) occurs, the first step in the chain of survival is detection. However, 75% of OHCAs are unwitnessed, representing the largest barrier to activating the chain of survival. Wearable devices have the potential to be "artificial bystanders," detecting OHCA and alerting 9-1-1. We sought to understand factors impacting users' willingness for continuous use of a wearable device through an online survey to inform future use of these systems for automated OHCA detection. Data were collected from October 2022 to June 2023 through voluntary response sampling. The survey investigated user convenience and perception of urgency to understand design preferences and willingness to adhere to continuous wearable use across different hypothetical risk levels. Associations between categorical variables and willingness were evaluated through nonparametric tests. Logistic models were fit to evaluate the association between continuous variables and willingness at different hypothetical risk levels. The survey was completed by 359 participants. Participants preferred hand-based devices (wristbands: 87%, watches: 86%, rings: 62%) and prioritized comfort (94%), cost (83%), and size (72%). Participants were more willing to adhere at higher levels of hypothetical risk. At the baseline risk of 0.1%, older individuals with prior wearable use were most willing to adhere to continuous wearable use. Individuals were willing to continuously wear wearable devices for OHCA detection, especially at increased hypothetical risk of OHCA. Optimizing willingness is not just a matter of adjusting for user preferences, but also increasing perception of urgency through awareness and education about OHCA.

Sustainable pyrolytic carbon negative electrodes for sodium-ion batteries

Considering both sustainability and potential applications in various industrial sectors, pyrolytic carbon from the recycling of organic solid wastes can play a significant part in the unfolding energy revolution. Further innovations in circular-economy waste loops can facilitate higher economic benefits and lower environmental impacts, where a number of opportunities for improving pyrolytic carbon by choices of precursors, easy regulation of pyrolysis conditions and potential post-treatments. Here we propose a method to synthesize sustainable high-quality nanotube-like pyrolytic carbon using waste pyrolysis gas from the decomposition of waste epoxy resin as precursor, and conduct the exploration of its properties for possible use as a negative electrode material in sodium-ion batteries. The obtained pyrolytic carbon shows better cycling and rate performance than benchmark commercial hard carbon, retaining ∼105 mA h g−1 after 2000 cycles at 100 mA g−1 and exhibiting ∼57 mA h g−1 at 1 A g−1. Since the slope-dominated nature of pyrolytic carbon leads to high performance dependence on defects and pore structure, we therefore also investigate the preferred design of pore structure via pore-forming by post-treatment. It is found that reversible adsorption/desorption on defect sites and optimal pore structure are highly needed for pyrolytic carbon toward practical applications. This work highlights the potential of waste pyrolysis gas itself as a valuable feedstock for the production of value-added carbon materials.

Potential and goal conflicts in reverse auction design for bioenergy with carbon capture and storage (BECCS)

Bioenergy with carbon capture and storage (BECCS) is considered as a future key technology to provide baseload electricity, heat, pulp, paper, and biofuels, while also enabling atmospheric carbon dioxide removal (CDR). Sweden seeks to lead the way in bringing this technology up to scale, introducing a EUR 3.6 billion reverse auction scheme to facilitate market entry of companies producing BECCS. We explore instrument design preferences among politicians, regulators, and prospective BECCS operators to identify trade-offs and explore feasible policy design. Based on 35 interviews with experts in the latent BECCS sector in Sweden, we identify under which circumstances prospective operators would be willing to place bids and discuss how actor preferences both align with and challenge auction theory. The analysis concludes that at least four dilemmas need attention. These concerns how to: (1) balance the state’s demand for BECCS to be implemented already in 2030 against the prospective BECCS operators’ fear of the winner’s curse, i.e., a fear of bidding for a contract that turns out to be too costly to implement; (2) allocate contracts at the margin of the auctioneer’s demand for BECCS without driving up costs; (3) design compliance mechanism to achieve effectiveness without undermining efficiency, and; 4) integrate the auction with the voluntary carbon market—if at all—in a manner that safeguards the environmental integrity of the auctions.

The treachery of green images? Using modular green system to analyse the gap between image perceptions and greenspace user behaviour

While user preferences for green space design have long remained a key subject of inquiry, most studies rely on evaluations of images due to the many challenges of creating actual green spaces for experimentation. However, researchers are increasingly aware of potential discrepancies between image perceptions and actual user behaviour, and many have thus called for more empirical analysis of how users actually interact with different green patterns to make knowledge of greenery design more valid. Although the difficulty of reconfiguring greenery in real open spaces has limited studies comparing image perceptions and actual visitors’ use, recent technological innovations in green infrastructure have made it possible to easily alter greenery layouts and compare the effectiveness of green space designs. Using both photo representations and a modular green system, we empirically tested and compared subject use and evaluations of three greenery patterns: no greenery (NO), open greenery (OP) and enveloping greenery (EN). Although the OP pattern was the most favourably evaluated on the basis of photos, our results indicate that the EN pattern has a significantly positive relationship with the number of visitors, compared with the OP and NO patterns. This finding suggests that subjective perceptions of photos or collages may not correspond to preferable greenery designs for users. Therefore, when developing new green spaces, the gap between images and actual use should be kept in mind and empirical design studies should be conducted in situ to make open spaces more attractive.

Safety impacts of design for manufacture and assembly techniques in off-site construction

Design for manufacture and assembly (DfMA) is an approach for improving project safety performance. For off-site construction (OSC), the philosophy is increasingly becoming a preferred design approach for OSC components. However, studies examining the safety impact of DfMA in OSC are limited. This study investigated the potential effects of DfMA techniques on mitigating specific safety hazards in OSC. A literature review identified and paired DfMA techniques and the safety hazards they mitigate. Empirical data was collected using a survey to assess the identified relationships. Data was analyzed using a combination of frequencies, inferential statistics, and Cronbach’s alpha. Most respondents agreed that DfMA techniques control their pairwise safety hazards in OSC. To eliminate safety hazards and limit their socio-economic impact, contracting organisations engaged in OSC need to consider the application of DfMA in the manufacture, assembly, and disassembly processes of OSC. The study reaffirms the importance of implementing evidence-based DfMA techniques for mitigating safety hazards in developing countries where OSC is an emerging philosophy.

Product innovation design approach driven by implicit relationship completion via patent knowledge graph

Product innovation design process involves a great deal of discrete engineering knowledge, limiting the ability of designers to quickly utilize this knowledge to support design innovation. Nowadays, innovation design based on knowledge graphs has enhanced the ability to explore design knowledge, improving the efficiency of knowledge retrieval. Previous studies have focused on mining more design knowledge to enrich the knowledge graph overlooks the implicit relationships with potential value among design knowledge, wasting design resources. To address these issues, an approach for product innovation design based on implicit knowledge relationship completion in the patent knowledge graph is proposed, which explores the implicit relationships between design knowledge to provide new knowledge satisfying design preferences and enhance the innovativeness of solutions. First, a requirements-function-structure-benefit (RFSB) knowledge ontology is constructed and extracted from the benefit knowledge of patents to build the knowledge graph. Second, an implicit relationship completion model based on the similarity of function or benefit entities explores the implicit relationships, replacing structure entities directly connected to similar function or benefit entities to generate new relationships and outputs novel ideas. Third, a scheme improvement process based on the co-occurrence frequency of requirement and structure knowledge supplements neglected design preferences. Final, a pipeline inspection robot case study is further employed to verify the proposed approach, and a patent knowledge graph assisted design solution prototype system is developed to assist in the utilization of innovative design knowledge. Evaluation results show the significant design potential of the proposed approach in inspiring innovative thinking and knowledge reuse.

Preferences for Food Vouchers Among Adults with Low Incomes

ABSTRACT There is growing interest in understanding the optimal design of food voucher programs to impchange the word “All foods” in the Table to “SNAP-eligible” to be consistent with the language used in Table 2 and Figure 1rove diet quality and support chronic disease self-management. We examined preferences for voucher program design among adults with low incomes who participated in a randomized trial. Participants preferred vouchers eligible for all foods over those restricted to fruits and vegetables (p = .001) and a monthly over weekly redemption schedule (p = .003). Preferences differed significantly by voucher assignment (pinteraction < 0.0001 for both), with those assigned to the fruit and vegetable voucher more likely to prefer that voucher. Flexibility was identified as a key driver of preference.

Raising awareness about physical activity’s role in reducing cancer risk: qualitative interviews with immigrant women and community agency managers

ObjectivesTo explore how to reach immigrant women through community agencies to raise awareness of the role of physical activity (PA) in reducing cancer risk.Study designQualitative description.MethodsWe conducted semi-structured telephone interviews with immigrant women and community agency managers to discuss the ideal design of an education session on PA and cancer risk, and identified themes using content analysis.ResultsParticipants included 22 women (6 African or Caribbean Black, 4 Chinese, 3 Filipino, 5 Indian, 4 Pakistani) and 16 agency managers from across Canada. Women were not familiar with Canada’s PA guidelines, and few were aware that PA reduces the risk of cancer. All expressed interest in education about PA and cancer. Diverse women and managers expressed similar preferences for education session design including content (e.g. PA amount/type), format (e.g. in person preferred but virtual more practical), personnel (external expert plus agency staff), cultural tailoring (e.g. translated supplemental take home information) and reinforcing (e.g. follow-up with participants) strategies. Women and managers identified few barriers to participating in education sessions, chiefly, that women lacked time due to work and family responsibilities; and noted several enablers of participation (e.g. emphasize social aspect, provide gift cards or recreation centre passes).ConclusionsWe generated insight on the ideal characteristics of a community-based education session that could raise awareness among immigrant women of the importance of PA in reducing cancer risk. Further research is needed to assess the feasibility and impact of PA education sessions designed based on these findings.

Neural network extrapolation to distant regions of the protein fitness landscape

Machine learning (ML) has transformed protein engineering by constructing models of the underlying sequence-function landscape to accelerate the discovery of new biomolecules. ML-guided protein design requires models, trained on local sequence-function information, to accurately predict distant fitness peaks. In this work, we evaluate neural networks’ capacity to extrapolate beyond their training data. We perform model-guided design using a panel of neural network architectures trained on protein G (GB1)-Immunoglobulin G (IgG) binding data and experimentally test thousands of GB1 designs to systematically evaluate the models’ extrapolation. We find each model architecture infers markedly different landscapes from the same data, which give rise to unique design preferences. We find simpler models excel in local extrapolation to design high fitness proteins, while more sophisticated convolutional models can venture deep into sequence space to design proteins that fold but are no longer functional. We also find that implementing a simple ensemble of convolutional neural networks enables robust design of high-performing variants in the local landscape. Our findings highlight how each architecture’s inductive biases prime them to learn different aspects of the protein fitness landscape and how a simple ensembling approach makes protein engineering more robust.

Human-AI Teaming in Critical Care: A Comparative Analysis of Data Scientists' and Clinicians' Perspectives on AI Augmentation and Automation.

Artificial intelligence (AI) holds immense potential for enhancing clinical and administrative health care tasks. However, slow adoption and implementation challenges highlight the need to consider how humans can effectively collaborate with AI within broader socio-technical systems in health care. In the example of intensive care units (ICUs), we compare data scientists' and clinicians' assessments of the optimal utilization of human and AI capabilities by determining suitable levels of human-AI teaming for safely and meaningfully augmenting or automating 6 core tasks. The goal is to provide actionable recommendations for policy makers and health care practitioners regarding AI design and implementation. In this multimethod study, we combine a systematic task analysis across 6 ICUs with an international Delphi survey involving 19 health data scientists from the industry and academia and 61 ICU clinicians (25 physicians and 36 nurses) to define and assess optimal levels of human-AI teaming (level 1=no performance benefits; level 2=AI augments human performance; level 3=humans augment AI performance; level 4=AI performs without human input). Stakeholder groups also considered ethical and social implications. Both stakeholder groups chose level 2 and 3 human-AI teaming for 4 out of 6 core tasks in the ICU. For one task (monitoring), level 4 was the preferred design choice. For the task of patient interactions, both data scientists and clinicians agreed that AI should not be used regardless of technological feasibility due to the importance of the physician-patient and nurse-patient relationship and ethical concerns. Human-AI design choices rely on interpretability, predictability, and control over AI systems. If these conditions are not met and AI performs below human-level reliability, a reduction to level 1 or shifting accountability away from human end users is advised. If AI performs at or beyond human-level reliability and these conditions are not met, shifting to level 4 automation should be considered to ensure safe and efficient human-AI teaming. By considering the sociotechnical system and determining appropriate levels of human-AI teaming, our study showcases the potential for improving the safety and effectiveness of AI usage in ICUs and broader health care settings. Regulatory measures should prioritize interpretability, predictability, and control if clinicians hold full accountability. Ethical and social implications must be carefully evaluated to ensure effective collaboration between humans and AI, particularly considering the most recent advancements in generative AI.

Improving the understandability of flood warning messages – Explorative study on design preferences

Early warning systems (EWS) are effective if they prevent loss of lives, injuries and structural damage. Optimization of EWS is often focused on technical aspects such as the dissemination of warnings. Since the audience's response is key for the effectiveness of an EWS, non-technical aspects that improve perception and understandability of warning messages deserve attention, too. German warning messages have been criticized, particularly after fatal and destructive floods in July 2021, as being insufficient and not understandable. Data from an exploratory online survey in Germany (n = 131) reveal insights on preferences in flood warning message (FWM) design. The survey focused on structural appearance of recommendations on action and on graphic support like maps, symbols and photos. Respondents showed clear preferences of including graphics into FWMs (96 %) and structuring recommendations on action in a bullet point format (85 %). Maps were the most favored among the offered graphic options, as they offer visual information on e.g., intensity and extent of inundation. Display of real time flood maps is often not feasible yet, but flood hazard maps are available in Germany and could be integrated into future FWM as an intermediate solution.

Learning analytics dashboard design: Workplace learner preferences for reference frames in immersive training in practice

AbstractBackgroundLearning analytics dashboards are increasingly being used to communicate feedback to learners. However, little is known about learner preferences for dashboard designs and how they differ depending on the self‐regulated learning (SRL) phases the dashboards are presented (i.e., forethought, performance, and self‐reflection phases) and SRL skills. Insight into design preferences for dashboards with different reference frames (i.e., progress, social, internal achievement and external achievement) is important because the effectiveness of feedback can depend upon how a learner perceives it.ObjectiveThis study examines workplace learner preferences for four dashboard designs for each SRL phase and how SRL skills relate to these preferences.MethodsSeventy participants enrolled in a chemical process apprenticeship program took part in the study. Preferences were determined using a method of adaptive comparative judgement and SRL skills were measured using a questionnaire. Preferences were tested on four dashboard designs informed by social and temporal comparison theory and goal setting theory. Multinomial logistic regressions were used to examine the relationship between dashboard preferences and SRL.Results and ConclusionsResults show that the progress reference frame is more preferred before and after task performance, and the social reference frame is less preferred before and after task performance. It was found that the higher the SRL skill score the higher the probability a learner preferred the progress reference frame compared to having no preference before task performance. The results are consistent with other findings, which suggest caution when using social comparison in designing dashboards which provide feedback.

Analysis of Articles on the Nature of Science between 2015 and 2022

It is evident that knowing the nature of science is a requirement for “science education”, which serves as the basis of conscious citizenship. For this reason, articles concerning the nature of science that were published in the Web of Science and EBSCOhost database between 2015 and 2022 were examined in this study in order to establish a broad framework and develop a research road map. A qualitative design approach and a descriptive review method were used. The keywords "Nature of Science (NoS) and Science Education" and "Teaching of Nature of Science (NoS) and Science Education" were used. The majority of the 107 articles on the nature of science that have been examined preferred qualitative research designs, and "Science &amp;amp; Education" is the publication that has published the most articles on the subject in 2017-2018-2020, pre-service teachers were mostly preferred as the sample group, it was applied to groups of “21-50” people as the sample group, open reflective approach was preferred as the teaching approach, the most commonly used method-technique was “discussion”, the activities used in the articles were generally standard, semi-structured interview form was preferred as the evaluation tool and “VNOS-C” was deployed as the questionnaire. Studies may be conducted within the boundaries of further lectures on the topic and internationally published theses.

Enhancing Productivity through Optimized Reading Spaces

In today's fast-paced, information-driven world, productivity is paramount for personal and professional success. Effective reading, a crucial cognitive process, significantly impacts knowledge acquisition, critical thinking, and innovation. This research offers an extensive examination of optimizing reading spaces to boost productivity. The study investigates the intricate relationship between reading environments and cognitive performance, considering factors like lighting, ergonomics, acoustics, spatial layout, and technology integration. These elements profoundly influence reader engagement, information retention, and cognitive load. Moreover, the study delves into environmental psychology's role in shaping concentration, creativity, and comfort within reading spaces. It analyzes the psychological effects of design elements like color, nature, and organization on cognitive processes. Understanding these responses empowers designers and individuals to tailor spaces for better focus and well-being. The integration of technology within reading spaces is explored, assessing digital platforms, interactive displays, and personalized content curation's benefits for efficient information consumption. It addresses challenges in balancing printed materials and digital resources. Additionally, the study considers personalized reading spaces' impact on diverse demographic groups, accounting for age, cognitive abilities, and preferences in design and customization. It emphasizes adaptable spaces catering to various needs and learning styles. This research offers a comprehensive view of reading spaces and productivity enhancement. By examining design elements, psychological factors, and technological integration, it provides insights for creating spaces that empower individuals to engage effectively with information, think critically, and achieve higher productivity in academic and professional endeavors.