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.     

An integrated dimensionality reduction and surrogate optimization approach for plant-wide chemical process operation

With liquefied natural gas becoming increasingly prevalent as a flexible source of energy, the design and optimization of industrial refrigeration cycles becomes even more important. In this article, we propose an integrated surrogate modeling and optimization framework to model and optimize the complex CryoMan Cascade refrigeration cycle. Dimensionality reduction techniques are used to reduce the large number of process decision variables which are subsequently supplied to an array of Gaussian processes, modeling both the process objective as well as feasibility constraints. Through iterative resampling of the rigorous model, this data-driven surrogate is continually refined and subsequently optimized. This approach was not only able to improve on the results of directly optimizing the process flow sheet but also located the set of optimal operating conditions in only 2 h as opposed to the original 3 weeks, facilitating its use in the operational optimization and enhanced process design of large-scale industrial chemical systems.     

TCBR-HMM: An HMM-based text classifier with a CBR system

This paper presents an innovative solution to model distributed adaptive systems in biomedical environments. We present an original TCBR-HMM (Text Case Based Reasoning-Hidden Markov Model) for biomedical text classification based on document content. The main goal is to propose a more effective classifier than current methods in this environment where the model needs to be adapted to new documents in an iterative learning frame. To demonstrate its achievement, we include a set of experiments, which have been performed on OSHUMED corpus. Our classifier is compared with Naive Bayes and SVM techniques, commonly used in text classification tasks. The results suggest that the TCBR-HMM Model is indeed more suitable for document classification. The model is empirically and statistically comparable to the SVM classifier and outperforms it in terms of time efficiency.     

基于桥连接的词典学习方法的语义解析

现阶段的语义解析方法大部分都基于组合语义,这类方法的核心就是词典。词典是词汇的集合,词汇定义了自然语言句子中词语到知识库本体中谓词的映射。语义解析一直面临着词典中词汇覆盖度不够的问题。针对此问题,该文在现有工作的基础上,提出了基于桥连接的词典学习方法,该方法能够在训练中自动引入新的词汇并加以学习,为了进一步提高新学习到的词汇的准确度,该文设计了新的词语—二元谓词的特征模板,并使用基于投票机制的核心词典获取方法。该文在两个公开数据集(WebQuestions和Free917)上进行了对比实验,实验结果表明,该文方法能够学习到新的词汇,提高词汇的覆盖度,进而提升语义解析系统的性能,特别是召回率。     

Recent activities in the field of Nuclear Operational Management and Nuclear Safety Engineering

Recent activities in the field of Nuclear Operational Management and Nuclear Safety Engineering, the studies related to risk analysis methodology, design, and operational management, physical phenomena, and emergency preparedness and nuclear security, have been progressed. Especially, ‘risk analysis methodology’ and ‘design and operational management’ are the main categories of the field, in which more than half of published articles on Journal of Nuclear Science and Technology are related to these categories.     

提高催化裂化装置(FCCU)柴汽比措施

为了满足市场的需要,中石化天津分公司炼油厂根据FCCU自身特点采取了一系列提高柴汽比的措施,包括:调节反应系统和分馏的操作条件及采用MGD技术,以提高柴油产率。实施后,FCCU的柴汽比从0.5提高到0.9,创造了良好的经济效益。     

宽工作电压范围单电源CMOS误差放大器

采用0.8μm标准数字CMOS工艺(VTN0=0.836V,VTP0=0.930V),设计并流片验证了具有宽工作电压范围(3～6V),可作SOC系统动态电源管理芯片内部误差放大器应用的单电源CMOS运算放大器。该误差放大器芯核同时具有适合低电压工作,并对工艺参数变化不敏感的优点。对于相同的负载情况,在3V的工作电压下,开环电压增益AD=83.1dB,单位增益带宽GB=2.4MHz,相位裕量Φ=85.2°,电源抑制比PSRR=154.0dB,转换速率Sr=2.2V/μs;在6V工作电压下,AD=85.1dB,GB=2.4MHz,Φ=85.4°,PSRR=145.3dB,Sr=3.4V/μs。     

带类型λ—演算

一、引言补演算是一个用函数描述计算的形式理论体系[1J,它由许多计算模型所组成。文〔1〕指出,应用认-演算比纯粹补演算更接近程序语言.但是由于内建函子和常数的引入常会发生一些问题,例如.常数O和函子+在机器中同样看待     

明末儒将朱舜水的园林花木趣味及他对东京小石川后乐园的贡献

朱舜水为明末清初进步思想家，博学多艺。他在力争复明抗清失败后流亡日本，对日本近世文化做出了巨大贡献。本文在概 括朱舜水对日本文化诸多方面所做贡献的基础上，分析了他的园林花木趣味，澄清了他在小石川后乐园建造过程中所参与工作的项目 与内容。     

连续工作型电子装备战备完好性预计

从战略完好性的实际内涵出发，考虑到装备实际工作中可能处于不同的工作状态，因而其战略完好性模型也应有所有同。对于处于连续工作状态的电子装备，即使工作中发生故障，只要执行下次任务前能修好，就不影响装备的战略完好性。基于此，得出了电子装备处于连续工作状态下的战略完好性预计模型，并在对应的条件下对此模型的得出进行了缜密的推理。