A method of constructing an inspiration library driven by user-perceived preference evaluation data for biologically inspired design

Biologically inspired design (BID) is one of the common methods for product design. To solve the problem of inaccurate acquisition of inspirational creatures due to the lack of user perception preference analysis, a data-driven intelligent service model for BID considering user perception needs is proposed based on Kansei engineering. Firstly, by extracting the perceptual features of creatures from the semantic source elements of products through mapping and encodes them, we proposed a data acquisition method based on intuitionistic fuzzy sets considering different customer preference distributions, bridging the gap caused by the asymmetry between designers and users. Secondly, the functional relationship between biometric features and user-perceived attributes is identified and predicted, and a predictive model of biodata considering user preferences is obtained by multiple linear regression analysis. Finally, based on the data clustering and reorganization theory to understand the organization and dynamics of the database, the construction of a BID library was completed, and the design resources in the library were used as analyzed knowledge for designers to plan design activities. Taking the bionic design of a UAV product as an example, a prototype of a computer-aided design service system was developed based on the theory proposed in the article, and the analyzed knowledge was used to improve the efficiency and science of the design, effectively verifying the usefulness of this study for design. To a certain extent, this study addresses the problem of cognitive limitations of designers and cognitive differences between designers and users, promotes the application of bioinspiration in product design, and improves the marketability of design solutions.     

犹豫模糊环境下准则具有偏好关系的TODIM方法

针对智慧制造评估时专家的决策信息具有犹豫模糊不确定性问题，提出了一种关于准则具有犹豫模糊偏好关系的改进交互式多准则决策（TODIM）方法。首先提出了准则间的犹豫模糊偏好关系概念，并证明了其基本性质。在TODIM方法优势度的计算过程中，将准则权重犹豫模糊偏好关系替代原有的精确值权重，使信息的准确性最大化。将该方法用于智能制造的评估上，实例分析结果表明所提方法是可行和有效的。     

不同热解工艺下半焦的微观结构特点及其对燃烧性能的影响

摘要：对比研究了3种直立内热炉半焦(熄焦方式分别为水泡熄焦、喷水熄焦及烟气干熄焦)及一种流化床热解半焦的微观结构及燃烧性能。通过对半焦组成、孔隙结构、有机官能团、碳化学结构及半焦微晶结构分析，获得了不同低温热解工艺半焦的组成及微观结构特点，明确了组成及微观结构与燃烧性能之间的关系。结果表明，不同热解工艺半焦的组成和微观结构差异明显，其对半焦的燃烧性能影响显著。干熄焦碳化学结构缺陷比例大，快速热解半焦孔隙结构发0达、挥发分高，与水喷焦相比水泡焦石墨化程度低；水喷焦燃烧性能优于水泡焦，干法所得半焦的燃烧性优于湿法；半焦的挥发分含量决定其燃点，在快升温速率条件下孔隙结构对半焦的燃烧性能影响较大，而慢升温速率条件下有序化度对半焦的燃烧性能影响较大。     

三塘湖盆地中—下侏罗统煤层甲烷风化带划分

以三塘湖盆地中、低煤阶煤层含气量和主要气体成分为基础,结合盆地构造、沉积及水文地质特征,对汉水泉凹陷和条湖凹陷煤层甲烷风化带进行了划分,并对库木苏凹陷、马朗凹陷、淖毛湖凹陷和苏鲁克凹陷煤层甲烷风化带进行了预测。结果表明,三塘湖盆地甲烷风化带深度为400~1000 m.由于受东北冲断隆起带的影响,三塘湖盆地北部甲烷风化带浅于南部。沉积方面,盆地东部淖毛湖凹陷、马朗凹陷和条湖凹陷深湖—半深湖和辫状河三角洲成煤环境优于盆地西部汉水泉凹陷和库木苏凹陷扇三角洲成煤环境,盆地东部甲烷风化带普遍浅于西部;水文地质方面,条湖凹陷和马朗凹陷中开启性局部滞留水文地质单元形成的甲烷风化带浅于其他凹陷封闭性弱径流水文地质单元的甲烷风化带。初步预测马朗凹陷北部为下一步煤层气勘探开发的优势区块,条湖凹陷北部为下一步煤系气勘探开发的优势区块。     

不同煤阶煤孔隙特征及其吸附能力响应

我国是煤炭资源大国，煤层气储量规模相当可观，但煤储层又具有低孔、低渗的不足，照搬国外或常规石油天然气的开采程序和方法已被证实是走不通的。应结合实际，根据不同地质条件、不同煤阶的开采程序，进行孔隙特征研究。煤孔隙特征、连通性和吸附能力对煤层气开采影响尤为重要，为研究煤孔隙结构特征随煤变质程度的变化关系及其吸附能力的响应特点，采取不同地区不同变质程度煤样，进行压汞测试和等温吸附实验。实验结果表明，煤孔隙度和平均孔径均随变质程度增加呈现降低—升高—降低的趋势；煤中孔隙连通性随煤变质程度增加逐渐变差；随煤变质程度增加，其最大吸附能力也呈现降低—升高—降低的总体趋势。     

Integrated rough VIKOR for customer-involved design concept evaluation combining with customers’ preferences and designers’ perceptions

Customer-involved design concept evaluation (DCE) allows customers to take part in evaluating the design alternatives to get more popular design concept. Traditional customer-involved DCE methods still focus on the collection of customer responses and only consider cost and benefit characteristics of design criteria in multi-criteria decision-making (MCDM) based evaluation process. Few studies have customized the decision-making algorithms specifically aimed at customers’ preferences. This paper further explores the customers’ influences in the early stages of the product design development, and proposes a new rough number based MCDM model (i.e., VIKOR) incorporating customers’ preferences for design specifications along with designers’ perceptions for the characteristics of design criteria (cost and benefit) to perform concept evaluation under subjective environment, and this proposed method is named as integrated rough VIKOR (IR-VIKOR). The objective of this study is to identify the best design concept which maximizes the satisfactions of expectations from most customers as well as conforms to the characteristics of design criteria. Firstly, Shannon entropy is used to obtain the weightings and relative importance ratings of design criteria from the customers’ preferences. Secondly, the customers’ preferences for design attribute values, the importance ratings of design criteria and the characteristics of design criteria are combined together to define the ideal solutions to calculate the rough evaluation index of each design alternative in IR-VIKOR, and finally the ranking result is provided by IR-VIKOR to determine the best design concept. A practical design example is introduced to illustrate the evaluation process of this proposed method, and the empirical comparisons are further carried out to validate its superiority for DCE. Through the sensitivity analysis experiments including i) inside IR-VIKOR, and ii) between IR-VIKOR and other classical MCDM methods, the proposed method is proved to be a reliable and feasible customer-involved DCE approach.     

Structural characteristics and flammability of low-order coal pyrolysis semi-coke

This study focused on the effects of pyrolysis temperature on the structural characteristics and combustion properties of low rank coal. The combustion performance of semi-coke at different temperatures was studied by using low-temperature pyrolysis technology and non-isothermal thermogravimetric analysis. The variation of functional groups and carbon structure was quantitatively analyzed. The results show that the temperature has a significant effect on the semi-coke structure and flammability. In the middle and low temperature pyrolysis stage, the removal of water, volatile matter and functional groups is mainly carried out, and the degree of condensation and graphitization of carbon atoms is not obvious. The semi-coke performance with a pyrolysis temperature of 1023K is close to that of anthracite. The pyrolysis process is accompanied by the destruction of carbonaceous and the formation of mesopores, which affects the combustion performance. As the temperature increases, the flammability of the semi-coke is lowered, and the chemical structure of the semi-coke is a major factor affecting the flammability. The method of Coast-Redfern integration was used to calculate the kinetic parameters of the semi-coke. As the pyrolysis temperature increases, the activation energy of the combustion reaction increases, which is consistent with the trend of combustion performance change.     

EMA-PRBDS: efficient multi-attribute packet rank based data scheduling in wireless sensor networks for real-time monitoring systems

ABSTRACT

In recent years, Wireless Sensor Networks (WSNs) are widely placed in real-time monitoring systems like environmental, structural, patient monitoring, etc. The major criterion for WSN includes energy efficiency and network lifetime. Scheduling is used as a large number of data packets focus on the same queue at the same time. Only limited data scheduling schemes have been implemented in WSN to enhance the performance. The existing First Come First Serve (FCFS) and Dynamic Multilevel Priority (DMP) have some technical challenges like delay, packet drop and high energy consumption due to starvation and deadlock. In this paper, we proposed a new algorithm to optimise and rank the incoming data packets based on multi-attributes decision-making methodology named as Packet Rank Based Data Scheduling (PRBDS), the algorithm selects packet priority, deadline, and size as the metrics to rank the incoming data packets. A simulation result shows when compared with existing scheduling, PRBDS not only provides less energy consumption, also significantly reduces the packet drop and increases the lifetime. Thus, the proposed algorithm is most suitable for real-time monitoring system since it combines data ranking method with scheduling algorithm to create accurate and reliable results to evaluate the incoming data packets.     

Gender difference in color preference across cultures: An archetypal pattern modulated by a female cultural stereotype

A gender difference in color preference among British participants has been repeatedly reported, in which both males and females show a preference for blue‐green colors, while females express an additional preference for pink‐purple colors. To investigate the robustness of gender difference in color preference in a different culture, we tested 81 young adult Indians from a school of design and compared them to 80 young British students in Psychology. The 35‐item International Personality Item Pool (IPIP) and Bem Sex Role Inventory (BSRI) questionnaires were also administered to explore possible links between personality traits, gender schemata, and color preferences. Results confirmed a gender difference in both cultures; participants collectively expressed a preference for cool over warm colors, while in addition females showed a preference for pink colors, with a warm bias for Indian females and a cool bias for British females. While these results extend gender difference to Indian culture and support the universality of an underlying pattern they also reveal a culture‐specific contribution essentially observed in females. In British participants, color preference was correlated exclusively with BSRI scores in females and overwhelmingly with IPIP scores in males; this gender‐specific pattern of correlation was not replicated in the Indian sample. Results point to an archetypal pattern of gender difference in color preference with a remarkable cross‐cultural similarity in men and a subtle but significant cultural difference in women whose origin is yet to be explained.