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Surgical robotics: A look-back of latest advancement and bio-inspired ways to tackle existing challenges

Yang LIU, Jing LIU

《机械工程前沿（英文）》 2012年第7卷第4期页码 376-384 doi: 10.1007/s11465-012-0352-1

摘要：

This article is dedicated to present a review on existing challenges and latest developments in surgical robotics in attempts to overcome the obstacles lying behind. Rather than to perform an exhaustive evaluation, we would emphasize more on the new insight by digesting the emerging bio-inspired surgical technologies with potentials to revolutionize the field. Typical approaches, possible applications, advantages and technical challenges were discussed. Evolutions of surgical robotics and future trends were analyzed. It can be found that, the major difficulties in the field of surgical robots may not be properly addressed by only using conventional approaches. As an alternative, bio-inspired methods or materials may shed light on new innovations. While endeavors to deal with existing strategies still need to be made, attentions should be paid to also borrow ideas from nature.

关键词： minimally invasive surgery surgical robotics haptic feedback miniaturization bio-inspiration bionics

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Engineering platelet-mimicking drug delivery vehicles

Quanyin Hu, Hunter N. Bomba, Zhen Gu

《化学科学与工程前沿（英文）》 2017年第11卷第4期页码 624-632 doi: 10.1007/s11705-017-1614-6

摘要： Platelets dynamically participate in various physiological processes, including wound repair, bacterial clearance, immune response, and tumor metastasis. Recreating the specific biological features of platelets by mimicking the structure of the platelet or translocating the platelet membrane to synthetic particles holds great promise in disease treatment. This review highlights recent advancements made in the platelet-mimicking strategies. The future opportunities and translational challenges are also discussed.

关键词： drug delivery platelets nanomedicine bio-inspired biomimetic

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海豚群算法 Article

Tian-qi WU,Min YAO,Jian-hua YANG

《信息与电子工程前沿（英文）》 2016年第17卷第8期页码 717-729 doi: 10.1631/FITEE.1500287

摘要：群体智能算法采取分布式解决问题的策略，已成功应用于很多传统算法难以解决的优化问题。目前已有粒子群算法、遗传算法、蜂群算法、蚁群算法等已经成功实现且效果良好的算法，但在优化对象日益复杂的今天，这些算法越来越难以满足人们对精度和时间的要求，而改进这些算法所带来的收益也越来越低。在这种情况下，设计一种新的算法来更好地解决优化问题变得越来越有意义。海豚有很多值得关注的生物特性和生活习性，如回声定位、信息交流、合作分工等。通过将这些生物特性和生活习性与群体智能的思想结合起来，引入优化问题中，我们提出了一种新的算法——海豚群算法，并给出了算法的相关定义，详细阐述了算法中搜寻、呼叫、接受、捕猎四个关键阶段。为了验证海豚群算法的效果，使用了10个性质各异的基准函数对海豚群算法以及粒子群算法、遗传算法、蜂群算法进行实验，并将4个函数的收敛速度和基准函数结果进行比较。实验结果表明，海豚群算法在大多数情况下，特别是在低维单峰函数、高维多峰函数、步长函数、带随机变量的函数中表现良好，具有收敛速度先慢后快、阶段性收敛、不易陷入局部最优、对基准函数具体性质没有要求等特点，尤其适用于适应度函数调用次数较多、使用个体较少的优化问题。

关键词：仿生算法；海豚；优化

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互易域上的仿生密码系统：DNA链变异以保护健康数据 Research Articles

S. AASHIQ BANU, Rengarajan AMIRTHARAJAN

《信息与电子工程前沿（英文）》 2021年第22卷第7期页码 940-956 doi: 10.1631/FITEE.2000071

摘要：医疗保健和远程医疗行业依赖于互联网技术，数字健康数据更易受到网络攻击，因其中包含大量个人数据，因而，有必要保护数字医疗图像以及保证其安全传输。本文采用基于洛伦兹和吕混沌吸引子突变的DNA加密技术生成强伪随机密钥流。为增强混淆与扩散阶段的近似性系数，所提的混沌DNA加密系统在整数小波变换域和一个生物启发的交叉变异单元上运行。进而，使用组合演化吸引子中的量化混沌集进行异或运算。该算法可以获得平均信息熵7.9973，几乎接近于零相关性的像素变化率（number of pixel change rate, NPCR）99.642%，归一平均强度变化（unified average change in intensity, UACI）33.438%，以及密钥空间10203。此外，实验分析和基于美国国家标准与技术研究院（NIST）的统计测试套件测试证实，所提医疗图像加密技术具有抵御任何统计、差分和暴力攻击的能力。

关键词：医学图像加密；DNA；混沌吸引子；交叉；突变；电子医疗

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微小型机器鼠仿鼠行为学习与生成

高子航, 贾广禄, 谢宏钊, 黄强, 福田敏男, 石青

《工程（英文）》 2022年第17卷第10期页码 232-243 doi: 10.1016/j.eng.2022.05.012

摘要：

现有的仿生机器鼠仅可以执行一些基本的仿鼠运动基元（MP），并通过这些基元的刚性组合来形成简单的行为。为了模拟具有高相似性的典型实验鼠行为，本文提出使用概率模型和运动特征对实验鼠的行为进行参数化。首先，对15 个10 min 的实验鼠运动视频片段的分析表明，一只实验鼠在野外通常有6 种典型的行为，且每种行为都包含8 个运动基元的不同组合。本文首先使用softmax 分类器来获得实验鼠的行为-运动分层概率模型。其次，使用静态和动态的运动参数对运动基元组合进行特征化。本文分别使用分层聚类和模糊C均值（FCM）聚类获得静态和动态运动参数的优势值。这些优势值通过二阶傅里叶级数对实验鼠的脊柱关节轨迹进行拟合，并且通过具有两个隐藏层的反向传播（BP）神经网络对关节轨迹进行泛化。最后，将分层概率模型和泛化的关节轨迹分别作为控制策略和指令映射到机器鼠。本文在机器鼠上实现了6 种典型的仿鼠行为，其结果与实验鼠的行为相比显示出高度相似性。

关键词：仿生学微小型机器鼠神经网络学习行为生成

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无次要路径主动噪声控制系统的生物启发式与内点混合法 None

Muhammad Asif Zahoor RAJA, Muhammad Saeed ASLAM, Naveed Ishtiaq CHAUDHARY, Wasim Ullah KHAN

《信息与电子工程前沿（英文）》 2018年第19卷第2期页码 246-259 doi: 10.1631/FITEE.1601028

摘要：开发了一种主动噪声控制（active noise control，ANC）系统的混合计算框架，运用基于遗传算法（genetic algorithm，GA）和内点法（interior-point method，IPM）的进化计算技术，集成得到GA-IPM方法。标准ANC系统通常采用滤波扩展最小均方算法优化线性有限脉冲响应滤波器的系数，但易陷入局部极小值（local minima，LM）。本文提出的GA-IPM计算方法有效解决了上述问题。该法不易出现LM问题，且无需识别方案中ANC系统的次级路径。采用正弦、随机和复杂随机噪声干扰下的耳机ANC模型，对该方法在几种线性和非线性主级和次级路径状况下的表现进行评估。大量独立运行算法的统计分析结果验证了该方案的准确性和收敛性。

关键词：主动噪声控制（ANC）；过滤扩展最小均方（FXLMS）；模拟计算；遗传算法；内点法

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Novel quantum-inspired firefly algorithm for optimal power quality monitor placement

Ling Ai WONG,Hussain SHAREEF,Azah MOHAMED,Ahmad Asrul IBRAHIM

《能源前沿（英文）》 2014年第8卷第2期页码 254-260 doi: 10.1007/s11708-014-0302-1

摘要： The application of a quantum-inspired firefly algorithm was introduced to obtain optimal power quality monitor placement in a power system. The conventional binary firefly algorithm was modified by using quantum principles to attain a faster convergence rate that can improve system performance and to avoid premature convergence. In the optimization process, a multi-objective function was used with the system observability constraint, which is determined via the topological monitor reach area concept. The multi-objective function comprises three functions: number of required monitors, monitor overlapping index, and sag severity index. The effectiveness of the proposed method was verified by applying the algorithm to an IEEE 118-bus transmission system and by comparing the algorithm with others of its kind.

关键词： quantum-inspired binary firefly algorithm topological monitor reach area power quality

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Creative design inspired by biological knowledge: Technologies and methods

Runhua TAN, Wei LIU, Guozhong CAO, Yuan SHI

《机械工程前沿（英文）》 2019年第14卷第1期页码 1-14 doi: 10.1007/s11465-018-0511-0

摘要： Biological knowledge is becoming an important source of inspiration for developing creative solutions to engineering design problems and even has a huge potential in formulating ideas that can help firms compete successfully in a dynamic market. To identify the technologies and methods that can facilitate the development of biologically inspired creative designs, this research briefly reviews the existing biological-knowledge-based theories and methods and examines the application of biological-knowledge-inspired designs in various fields. Afterward, this research thoroughly examines the four dimensions of key technologies that underlie the biologically inspired design (BID) process. This research then discusses the future development trends of the BID process before presenting the conclusions.

关键词： creative design biologically inspired methods key technologies

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Assessment of novel nature-inspired fuzzy models for predicting long contraction scouring and related

《结构与土木工程前沿（英文）》 2021年第15卷第3期页码 665-681 doi: 10.1007/s11709-021-0713-0

摘要： The scouring phenomenon is one of the major problems experienced in hydraulic engineering. In this study, an adaptive neuro-fuzzy inference system is hybridized with several evolutionary approaches, including the ant colony optimization, genetic algorithm, teaching-learning-based optimization, biogeographical-based optimization, and invasive weed optimization for estimating the long contraction scour depth. The proposed hybrid models are built using non-dimensional information collected from previous studies. The proposed hybrid intelligent models are evaluated using several statistical performance metrics and graphical presentations. Besides, the uncertainty of models, variables, and data are inspected. Based on the achieved modeling results, adaptive neuro-fuzzy inference system–biogeographic based optimization (ANFIS-BBO) provides superior prediction accuracy compared to others, with a maximum correlation coefficient (R_test = 0.923) and minimum root mean square error value (RMSE_test = 0.0193). Thus, the proposed ANFIS-BBO is a capable cost-effective method for predicting long contraction scouring, thus, contributing to the base knowledge of hydraulic structure sustainability.

关键词： long contraction scour prediction uncertainty ANFIS model meta-heuristic algorithm

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Deep convolutional tree-inspired network: a decision-tree-structured neural network for hierarchical

《机械工程前沿（英文）》 2021年第16卷第4期页码 814-828 doi: 10.1007/s11465-021-0650-6

摘要： The fault diagnosis of bearings is crucial in ensuring the reliability of rotating machinery. Deep neural networks have provided unprecedented opportunities to condition monitoring from a new perspective due to the powerful ability in learning fault-related knowledge. However, the inexplicability and low generalization ability of fault diagnosis models still bar them from the application. To address this issue, this paper explores a decision-tree-structured neural network, that is, the deep convolutional tree-inspired network (DCTN), for the hierarchical fault diagnosis of bearings. The proposed model effectively integrates the advantages of convolutional neural network (CNN) and decision tree methods by rebuilding the output decision layer of CNN according to the hierarchical structural characteristics of the decision tree, which is by no means a simple combination of the two models. The proposed DCTN model has unique advantages in 1) the hierarchical structure that can support more accuracy and comprehensive fault diagnosis, 2) the better interpretability of the model output with hierarchical decision making, and 3) more powerful generalization capabilities for the samples across fault severities. The multiclass fault diagnosis case and cross-severity fault diagnosis case are executed on a multicondition aeronautical bearing test rig. Experimental results can fully demonstrate the feasibility and superiority of the proposed method.

关键词： bearing cross-severity fault diagnosis hierarchical fault diagnosis convolutional neural network decision tree

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Bio-based Technologies for Resource Recovery

Aijie Wang, David Stuckey

《环境科学与工程前沿（英文）》 2018年第12卷第4期 doi: 10.1007/s11783-018-1079-y

摘要：

关键词： valign= top class= J_zhaiyao

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concrete compressive strength prediction using adaptive neuro-fuzzy inference system optimized by nature-inspired

Ahmad SHARAFATI, H. NADERPOUR, Sinan Q. SALIH, E. ONYARI, Zaher Mundher YASEEN

《结构与土木工程前沿（英文）》 2021年第15卷第1期页码 61-79 doi: 10.1007/s11709-020-0684-6

摘要： Concrete compressive strength prediction is an essential process for material design and sustainability. This study investigates several novel hybrid adaptive neuro-fuzzy inference system (ANFIS) evolutionary models, i.e., ANFIS–particle swarm optimization (PSO), ANFIS–ant colony, ANFIS–differential evolution (DE), and ANFIS–genetic algorithm to predict the foamed concrete compressive strength. Several concrete properties, including cement content (C), oven dry density (O), water-to-binder ratio (W), and foamed volume (F) are used as input variables. A relevant data set is obtained from open-access published experimental investigations and used to build predictive models. The performance of the proposed predictive models is evaluated based on the mean performance (MP), which is the mean value of several statistical error indices. To optimize each predictive model and its input variables, univariate (C, O, W, and F), bivariate (C–O, C–W, C–F, O–W, O–F, and W–F), trivariate (C–O–W, C–W–F, O–W–F), and four-variate (C–O–W–F) combinations of input variables are constructed for each model. The results indicate that the best predictions obtained using the univariate, bivariate, trivariate, and four-variate models are ANFIS–DE– (O) (MP= 0.96), ANFIS–PSO– (C-O) (MP= 0.88), ANFIS–DE– (O–W–F) (MP= 0.94), and ANFIS–PSO– (C–O–W–F) (MP= 0.89), respectively. ANFIS–PSO– (C–O) yielded the best accurate prediction of compressive strength with an MP value of 0.96.

关键词： foamed concrete adaptive neuro fuzzy inference system nature-inspired algorithms prediction of compressive strength

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Biologically inspired model of path integration based on head direction cells and grid cells

Yang ZHOU,De-wei WU

《信息与电子工程前沿（英文）》 2016年第17卷第5期页码 435-448 doi: 10.1631/FITEE.1500364

摘要： Some neurons in the brain of freely moving rodents show special firing pattern. The firing of head direction cells (HDCs) and grid cells (GCs) is related to the moving direction and distance, respectively. Thus, it is considered that these cells play an important role in the rodents’ path integration. To provide a bionic approach for the vehicle to achieve path integration, we present a biologically inspired model of path integration based on the firing characteristics of HDCs and GCs. The detailed implementation process of this model is discussed. Besides, the proposed model is realized by simulation, and the path integration performance is analyzed under different conditions. Simulations validate that the proposed model is effective and stable.

关键词： Head direction cells (HDCs) Grid cells (GCs) Path integration Bionic navigation

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Combustion characteristics and kinetics of bio-oil

Ruixia ZHANG, Zhaoping ZHONG, Yaji HUANG

《化学科学与工程前沿（英文）》 2009年第3卷第2期页码 119-124 doi: 10.1007/s11705-009-0068-x

摘要： The combustion characteristics of bio-oils derived from rice husk and corn were studied by thermogravimetry analysis. According to the thermogravimetry (TG), differential thermogravimetry (DTG) and differential thermal analysis (DTA) curves of bio-oils in air and nitrogen atmosphere, we analyzed the combustion characteristics of different kinds of bio-oils in different atmospheres and worked out the combustion kinetics parameters of the bio-oil, providing reliable base data for the burning of bio-oil. The thermogravimetry indicated that the combustion process of bio-oil was divided into three stages. At the same time, the combustion process can be described by different order reaction models, and with the method of Coats-Redfern, the activation energy and frequency factor of different kinds of bio-oils were obtained.

关键词： bio-oil combustion characteristics combustion kinetics