Pattern design and optimization of yarn-dyed plaid fabric using isolation niche genetic algorithm and rough set theory

Under the circumstance of perceptual consumption, it is still challenging to grasp consumer's emotions and demands due to the large search space, diversified preferences, and easy fatigue of consumers. To reduce user fatigue and enlarge search space, a novel method was presented to design and optimize the pattern of yarn-dyed plaid fabric using the isolation niche genetic algorithm and rough set theory. Each pattern was encoded as a chromosome based on the real number code. The population was initialized and evolved using INGA to maintain the diversity. The rough set theory was adopted as the fitness function of isolation niche genetic algorithm to extract the consumer's demands. After multiple evolutions, a large set of practical patterns of the yarn-dyed plaid fabric are obtained. Experiments were carried out by 24 testers of different ages and genders. The results prove that the proposed method based on the isolation niche genetic algorithm and rough set theory is feasible and effective, supplying references to the designer.     

周期性隔震基础的优化设计与试验验证

周期性隔震基础是利用周期性结构的衰减域特性,将地震动与上部结构自振频率接近的频率范围内的能量衰减,从而控制上部结构响应的新型隔震装置。周期性基础的隔震性能受到多方面因素的影响,包括局域共振子的调谐频率比、质量比、阻尼比、基体的刚度、上部结构与基础的相互作用以及地震动的频谱特性等。目前尚未有研究综合考虑上述因素的影响并提出周期性基础的设计方法。提出以一组地震动作用下上部结构峰值响应衰减率的平均值为目标函数,对周期性基础进行优化的设计方法。计算结果表明,按照该优化方法得到的周期性基础对上部结构在选取的44条地震动作用下,峰值响应的平均衰减率达30%。参数敏感性分析表明,优化设计得到的周期性基础对于自身参数的变化具有良好的鲁棒性。最后利用缩尺振动台试验验证了优化设计得到的周期性基础的隔震性能,证明了优化方法的有效性和优化结果的正确性。     

TLCD基础隔震框架结构的减振控制研究

为了避免和减轻由过大隔震层位移引起的损害,对基础隔震框架结构装设调频液柱阻尼器(tuned liquid column damper,简称TLCD)后混合系统的减振效果进行研究。建立了单层和多层混合控制系统在地震作用下的运动方程,采用TLCD-结构体系转化为调频质量阻尼器(tuned mass damper,简称TMD)-结构体系的等效方法,利用TMD参数优化公式,得到单个TLCD初始设计参数,并采用状态空间方程得到多个TLCD最优设计参数。通过对某8层基础隔震结构进行模拟,证明了该理论设计方法的合理性。该混合结构不仅可以减小隔震层位移和加速度,而且对上部结构位移和加速度反应都能更有效的控制。     

Fault tolerant system based on non-integers order observers: Application in a heat exchanger

This work presents a fault-tolerant (FT) scheme based on the application of non-integer order observers also called fractional observers, the case of study is a double pipe countercurrent heat exchanger (HE). The aim of the FT is to detect sensors faults as soon as possible, and to provide a healthy signal in order to replace the faulty sensor signal by the fractional observer estimation. To develop the FT scheme a bank of high gain fractional order observers (HGFOO) is proposed. The Riemann-Liouville (RL) fractional derivative definition is used to solve each fractional observer. Experimental measures from a HE were used to test the performance of the fractional observers and the control scheme. The results show the robustness of the proposed observers.     

GreyFan:一种Wi-Fi隐蔽信道攻击框架

针对现实网络中诸如侧信道攻击、HID 攻击等传统的物理攻击，物理隔离被认为是一种较为彻底的抵御网络攻击的安全防护手段。2018 年，业界首次提出了一种物理隔离环境下的 Wi-Fi 隐蔽信道方法——Ghost Tunnel，即在Wi-Fi尚未连接的状态下，无线AP可成功将数据传给发起连接请求的计算机。提出了一种基于Ghost Tunnel方法的攻击框架—— GreyFan，利用该攻击框架攻击者可以对未连接Wi-Fi的用户实施无感知攻击，如文件隐蔽传输、任意代码执行等，并分析了相应的防御技术。     

Exploiting Bayesian networks for fault isolation: A diagnostic case study of diesel fuel injection system

Fault isolation is known to be a challenging problem in machinery troubleshooting. It is not only because the isolation of multiple faults contains considerable number of uncertainties due to the strong correlation and coupling between different faults, but often massive prior knowledge is needed as well. This paper presents a Bayesian network-based approach for fault isolation in the presence of the uncertainties. Various faults and symptoms are parameterized using state variables, or the so-called nodes in Bayesian networks (BNs). Probabilistically causality between a fault and a symptom and its quantization are described respectively by a directed edge and conditional probability. To reduce the qualitative and quantitative knowledge needed, particular considerations are given to the simplification of Bayesian networks structures and conditional probability expressions using rough sets and noisy-OR/MAX model, respectively. By adopting the simplified approach, symptoms under multiple-fault are decoupled into the ones under every single fault, while the quantity of the conditional probabilities is simplified into the linear form of the faults quantity. Prior knowledge needed in Bayesian network-based diagnostic model is reduced significantly, which decreases the complexity in establishing and applying this diagnosis model. The computational efficiency is improved accordingly in the simplified BN model, after eliminating the redundant symptoms. The fault isolation methodology is illustrated through an example of diesel engine fuel injection system to verify the developed model.     

Analysis of driver roles: modelling the changing role of the driver in automated driving systems using EAST

ABSTRACT

The purpose of this paper is to analyse the role of the driver within automated driving systems using the Event Analysis of Systemic Teamwork (EAST) method. We already know that as the level of automation increases within the driving task, the role of the driver shifts from that of an active operator (i.e. a driver driving) to more of a passive monitor (i.e. a driver monitoring). Task, social and information networks were constructed using the Hierarchical Task Analysis of Driving and evidence from driver verbalisations collected during a previous study to further explore the changing role of the driver using network analysis. A ‘broken links’ approach was conducted to show that momentary engagement in non-driving-related secondary tasks within an automated driving system can dramatically change the structure of driving system.     

Nonreciprocal properties of 1D magnetized plasma photonic crystals with the Fibonacci sequence

In this paper, the nonreciprocal properties of a novel kind of 1D magnetized plasma photonic crystals(MPPCs) with the Fibonacci sequence are investigated. The isolation of the proposed 1D MPPCs is also used to analyze the nonreciprocal properties. Compared to the conventional 1D MPPCs with periodic structure, the nonreciprocal performance can be significantly improved.The effects of several parameters of the proposed 1D MPPCs on the nonreciprocal properties are studied by the transfer matrix method, which includes the incident angle, order of the Fibonacci sequence, plasma frequency, plasma cyclotron frequency and plasma filling factor. The obtained results show that the nonreciprocal propagation properties can be improved by increasing the values of the plasma cyclotron frequency and incident angle, but they will worsen by blindly increasing the order of the Fibonacci sequence, plasma frequency and filling factor of plasma.The peaks of transmittance also are obviously reduced. In addition, the value of isolation will increase with increasing the incident angle, order of Fibonacci sequence, plasma frequency and plasma filling factor. However, when the plasma cyclotron frequency is increased, the value of isolation will be increased at lower frequencies, but is almost unchanged at higher frequencies.     

Value drivers of blockchain technology: A case study of blockchain-enabled online community

There is growing recognition that blockchain technology has significant potential to alter how organizations and people work and communicate. However, theoretical guidance concerning how organizations leverage blockchain technology to enhance value creation for users is still limited. Grounded in the socio-technical perspective and leveraging the rich data obtained from case analyses of blockchain-enabled online communities, this paper develops a theoretical model to identify the core value drivers that blockchain enables for online communities. The core value drivers include: a reputation-value system, data ownership mechanisms, and verification & tracking mechanisms. Our findings suggest that these three value drivers enhance value creation of online communities by motivating participation and protecting contributions.