Establishing product appearance specifications with the identification of user aesthetic needs in product conceptual design

This chapter presents the basic concepts of aesthetic needs and product specifications in conceptual design. The user aesthetics needs are considered one of the significant determinants in increasing user satisfaction. In this regard, the importance of establishing product appearance specifications to identify user aesthetic needs is discussed. A method is introduced to demonstrate the significance of considering aesthetic and emotional needs when establishing product appearance specifications in product conceptual design. To improve appearance specifications based on aesthetic experiences collected from users and designers, an approach using fuzzy logic is proposed and illustrated by a case study of digital camera design

A conceptual design specification based on user aesthetic information analysis and product functional reasoning

User satisfaction with a product plays a direct role in the purchasing decisions. With the enrichment of material life and the growth of individual requirements, this satisfaction is derived from the requirement for functionality to aesthetics. Conventional product design methods normally focus on achieving the required functions where its design specifications are mainly related to certain functional or usability requirements. In recent years, researchers have made efforts to develop methods for supporting aesthetic design activities during the product conceptual design phase. However, most of these methods hardly consider product aesthetics or the consumers’ emotional needs. Therefore, this study proposed a user-driven conceptual design specification integrating functional reasoning with aesthetic information analysis. The method consisted of two tasks, the construction of a mapping model and the implementation of the mapping model. Firstly, the mapping model was constructed for capturing the relationships between initial design specifications and user experience (UX). Secondly, the proposed design specifications were selected, refined, and optimized based on the mapping model. A case study on digital camera design was carried out to demonstrate the feasibility and effectiveness of the proposed method. The results showed that, compared with the initial design specification candidates, the UX was enhanced by applying the improved design specifications

Conceptual design of intelligent manufacturing equipment based on a multi-source heterogeneous requirement mapping method

Intelligent manufacturing equipment constitutes important prerequisite and foundation for processing and manufacturing. In its conceptual design process, functional determination based on customer needs (CAs), intelligence demands (IDs) and manufacture constraints (MCs) is the prerequisite and basis for subsequent design work. As these various requirement information becomes more complex and mixed, a practical design method will improve the design efficiency of this type of problem. Although research on requirement acquisition and transformation methods has been intensively studied, this problem is still difficult to solve by traditional methods due to the multi-source heterogeneous characteristics of requirement information. To overcome this problem, a requirements mapping methodology is proposed to decompose and transform multi-source heterogeneous requirements and map them to different functional knowledge (FK). Multi-source design requirements are categorized by different objectives such as manufacturing, customer, and intelligence, and these heterogeneous information is analyzed by the decomposition method corresponding to them. The conceptual scheme (CS) is derived through a four-step selection process: requirement set (RS) determination, FK mapping, knowledge combination, and scheme evaluation. The prototype design and an experimental study of a brand-new intelligent folding gantry crane is conducted. The results show that the proposed method can not only improve the design efficiency of intelligent manufacturing equipment, but also reduce the repetitive work in the detailed design stage

A quantitative aesthetic measurement method for product appearance design

Product appearance is one of the crucial factors that influence consumers’ purchase decisions. The attractiveness of product appearance is mainly determined by the inherent aesthetics of the design composition related to the arrangement of visual design elements. Hence, it is critical to study and improve the arrangement of visual design elements for product appearance design. Strategies that apply aesthetic design principles to assist designers in effectively arranging visual design elements are widely acknowledged in both academia and industry. However, applying aesthetic design principles relies heavily on the designer’s perception and experience, while it is rather challenging for novice designers. Meanwhile, it is hard to measure and quantify design aesthetics in designing artefacts when designers refer to existing successful designs. In this regard, this study aims to introduce a method that assists designers in applying aesthetic design principles to improve the attractiveness of product appearance. Furthermore, formulas for aesthetic measurement based on aesthetic design principles are also developed, and it makes an early attempt to provide quantified aesthetic measurements of design artefacts. A case study on camera design was conducted to demonstrate the merits of the proposed method where the improved strategies for the camera appearance design offer insights for concept generation in product appearance design based on aesthetic design principles

In Ovo Monitoring of Smooth Muscle Fiber Development in the Chick Embryo: Diffusion Tensor Imaging with Histologic Correlation

, and to determine the correlation between histologically-derived muscle fiber fraction, day of incubation and diffusion tensor imaging fractional anisotropy values and length of tracked fibers.From a set of 82 normally developing fertile chicken eggs, 5 eggs were randomly chosen each day from incubation days 5 to 18 and cooled using a dual-cooling technique prior to and during magnetic resonance imaging at 3.0 Tesla. Smooth muscle fibers of the gizzard were tracked using region of interests placed over the gizzard. Following imaging, the egg was cracked and the embryo was fixated and sectioned, and a micrograph most closely corresponding to the acquired magnetic resonance image was made. Smooth muscle fiber fraction was determined using an automated computer algorithm. development of smooth muscle tissue

Multi-indicators decision for product design solutions: a TOPSIS-MOGA integrated model

Design decisions occur in all phases of product design and largely affect the merits of the final solution, which will ultimately determine the success or failure of the product in the market. Product design is a continuous process, and a large number of existing studies have proposed decision methods and decision indicators for the characteristics of different stages of design. These methods and indicators can meet the requirements of one of the phases: demand analysis, conceptual design, or detailed design. However, further research can still be conducted on the integration of methods throughout the design phase, using intelligent design methods, and improving the design continuity and efficiency. To address this problem, a TOPSIS-MOGA-based multi-indicators decision model for product design solutions is proposed, including its product design process, decision algorithm, and selection method. First, a TOPSIS-MOGA integrated model for conceptual design and detailed design process is established, the continuity of decision-making methods is achieved by integrating decision indicators. Second, conceptual design solutions are selected through the technique for order of preference by similarity to ideal solution (TOPSIS), based on hesitant fuzzy linguistic term sets and entropy weight method. Finally, detailed design solutions are selected through a multiobjective genetic algorithm (MOGA), based on a polynomial-based response surface model and central combination experimental design method. A case study of the decision-making in the design of high-voltage electric power fittings is presented, the conceptual design phase and the detailed design phase are connected through the indicators, which demonstrates that the proposed approach is helpful in the decision-making of the product design solutions

A smart knowledge deployment method for the conceptual design of low-carbon products

As the consciousness of the global environment and sustainability has increased, low-carbon products have played a vital role in the transformation to a circular economy. Advanced smart design technology has enabled product designers to fulfill customer requirements by offering tailor-made functions and low-carbon solutions. However, although the existing approaches used in the conceptual design process can help in functional reasoning, knowledge modelling, and scheme evaluation, the smart reuse of knowledge, such as in design model improvement and concept scheme iteration for lower carbon emission, the corresponding process evaluation concerning carbon footprint has not been given sufficient attention. To resolve this, in this work, a smart knowledge deployment method is proposed for reasoning, configuring, and optimizing the conceptual scheme (CS) based on carbon emission evaluation and interaction. First, to match discretized knowledge, sub-function requirements after function decomposition are mapped with granular clustered knowledge into a matrix based on a requirement function knowledge deployment (RFKD) model. Second, the derived candidate concept schemes (CCSs) are selected in three steps: conflict-based primaries, configuration, and carbon footprint ranking. Finally, the initial conceptual scheme (ICS) with the lowest carbon emission is used as input for the interactive genetic algorithm (IGA) to better capture a comprehensive set of user feedback on potential candidate schemes through interactions. Accordingly, improvements are completed as intended. The prototype design and an experimental study of a brand-new friction-wear testing machine are conducted. The results suggest that the proposed approach could effectively reduce the carbon emissions of products obtained through CS and improve the convergence of the schemes produced via genetic operation

STP Models of Optimal Differential and Linear Trail for S-box Based Ciphers

Automatic tools have played an important role in designing new cryptographic primitives and evaluating the security of ciphers. Simple Theorem Prover constraint solver (STP) has been used to search for differential/linear trails of ciphers. This paper proposes general STP-based models searching for differential and linear trails with the optimal probability and correlation for S-box based ciphers. In order to get trails with the best probability or correlation for ciphers with arbitrary S-box, we give an efficient algorithm to describe probability or correlation of S-Box. Based on the algorithm we present a search model for optimal differential and linear trails, which is efficient for ciphers with S-Boxes whose DDTs/LATs contain entities not equal to the power of two. Meanwhile, the STP-based model for single-key impossible differentials considering key schedule is proposed, which traces the propagation of values from plaintext to ciphertext instead of propagations of differences. And we found that there is no 5-round AES-128 single-key truncated impossible differential considering key schedule, where input and output differences have only one active byte respectively. Finally, our proposed models are utilized to search for trails of bit-wise ciphers GIFT-128, DES, DESL and ICEBERG and word-wise ciphers ARIA, SM4 and SKINNY-128. As a result, improved results are presented in terms of the number of rounds or probabilities/correlations

Elevated limb-bud and heart development (LBH) expression indicates poor prognosis and promotes gastric cancer cell proliferation and invasion via upregulating Integrin/FAK/Akt pathway

The limb-bud and heart development (LBH) gene is a highly conserved, tissue-specific transcription cofactor in vertebrates that regulates multiple key genes in embryonic development. The role of LBH in various cancer types is still controversial, and its specific role and molecular mechanism in the oncogenesis of gastric cancer (GC) remains largely unexplored. In the present study, the prognostic significance and clinicopathological characteristics of LBH in GC was determined. The LBH mRNA expression was first investigated in four independent public datasets (TCGA-STAD, GSE15459, GSE29272, and GSE62254) and then validated with our samples at the protein level. LBH was overexpressed at both the mRNA and protein levels in cancer compared with normal tissues. High LBH expression was correlated with advanced T, N, and M stages. Kaplan–Meier analysis and log-rank test indicated that higher LBH expression was statistically correlated with shorter overall survival (OS) in the public datasets and our study samples. Univariate and multivariate Cox regression analysis showed that LBH was an independent prognostic biomarker for survival in TCGA-STAD, GSE15459, GSE62254 cohorts, and our GC patients. In vitro experiments showed that knockdown of LBH can significantly inhibit the proliferation and invasion of HGC-27 cells, while overexpression of LBH can significantly enhance the proliferation and invasion of BGC-823 cells. Gene Set Enrichment Analysis (GSEA), Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomics (KEGG) indicated that high LBH expression is associated with the PI3K-Akt pathway, focal adhesion, and extracellular matrix (ECM)-receptor interaction. Western blot analysis showed that knockdown of LBH significantly inhibited the expression of integrin α5, integrin β1, p-FAK, and p-Akt. Therefore, results from the present study indicate that LBH is a potential independent prognostic biomarker and promotes proliferation and invasion of GC cells by activating the integrin/FAK/Akt pathway

Conditionally Immortalized Mouse Embryonic Fibroblasts Retain Proliferative Activity without Compromising Multipotent Differentiation Potential

Mesenchymal stem cells (MSCs) are multipotent cells which reside in many tissues and can give rise to multiple lineages including bone, cartilage and adipose. Although MSCs have attracted significant attention for basic and translational research, primary MSCs have limited life span in culture which hampers MSCs' broader applications. Here, we investigate if mouse mesenchymal progenitors can be conditionally immortalized with SV40 large T antigen and maintain long-term cell proliferation without compromising their multipotency. Using the system which expresses SV40 large T antigen flanked with Cre/loxP sites, we demonstrate that mouse embryonic fibroblasts (MEFs) can be efficiently immortalized by SV40 large T antigen. The conditionally immortalized MEFs (iMEFs) exhibit an enhanced proliferative activity and maintain long-term cell proliferation, which can be reversed by Cre recombinase. The iMEFs express most MSC markers and retain multipotency as they can differentiate into osteogenic, chondrogenic and adipogenic lineages under appropriate differentiation conditions in vitro and in vivo. The removal of SV40 large T reduces the differentiation potential of iMEFs possibly due to the decreased progenitor expansion. Furthermore, the iMEFs are apparently not tumorigenic when they are subcutaneously injected into athymic nude mice. Thus, the conditionally immortalized iMEFs not only maintain long-term cell proliferation but also retain the ability to differentiate into multiple lineages. Our results suggest that the reversible immortalization strategy using SV40 large T antigen may be an efficient and safe approach to establishing long-term cell culture of primary mesenchymal progenitors for basic and translational research, as well as for potential clinical applications