Design of Evolvable Hardware for Robotic Navigation

This paper presents an integrated on line learning system to evolve programmable logic array (PLA) controllers for navigating an autonomous robot in a two dimensional environment. The integrated on line learning system consists of two learning modules: one is the module of reinforcement learning based on temporal difference learning based on genetic algorithms, and the other is the module of evolutionary learning based on genetic algorithms. The control rules extracted from the module of reinforcement learning can be used as input to the module of evolutionary learning, and quickly implemented by the PLA through on line evolution. The on line evolution has shown promise as a method of learning systems in complex environment. The evolved PLA controllers can successfully navigate the robot to a target in the two dimensional environment while avoiding collisions with randomly positioned obstacles.

Evolvable Hardware Based Software-Hardware Co-Designing Platform ECDP

Based on the theories of EA （Evolutionary Algorithm） and EHW （Evolvable Hardware）, we devise an EHW based software-hardware co designing platform ECDP, on which we provided standards for hardware system encoding and evolving operation designing, as well as circuit emulating tools. The major features of this system are： two layer-encoding of circuit structure, off-line evolving with software cmulation and the evolving of genetic program designing. With this system, we implemented the auto designing of sonic software-hardware systems, like the random number generator.

Robot navigation system using intrinsic evolvable hardware

Recently there has been great interest in the idea that evolvable system based on the principle of artifcial intelligence can be used to continuously and autonomously adapt the behaviour of physically embedded systems such as autonomous mobile robots and intelligent home devices. Meanwhile, we have seen the introduction of evolvable hardware(EHW): new integrated electronic circuits that are able to continuously evolve to adapt the chages in the environment implemented by evolutionary algorithms such as genetic algorithm(GA) and reinforcement learning. This paper concentrates on developing a robotic navigation system whose basic behaviours are obstacle avoidance and light source navigation. The results demonstrate that the intrinsic evolvable hardware system is able to create the stable robotiiuc behaviours as required in the real world instead of the traditional hardware systems.

基于能量最小化的CCGA焊点形态仿真研究

为了确定某陶瓷柱栅阵列(CCGA)器件实现高焊接可靠性时的工艺参数组合范围,并研究焊点形态随不同参数变化的规律,以钎料润湿角、钎料体积以及焊柱偏移量作为关键变量因素,利用基于能量最小化原理的Surface Evolver软件,计算了不同因素水平组合下的实际焊点形态,并对参数化建模过程进行了详细介绍。通过对比形态结果与焊点可接收标准,寻找能够产生合格焊点的参量范围,为实际焊点微连接生产工艺提供合理的工艺指导。

PBGA焊点形态对疲劳寿命的影响

通过Surface Evolver软件预测了塑料球栅阵列(PBGA)焊点形态,将焊点形态结果导入Ansys软件中进行-55~125℃热循环仿真实验,通过Coffin-Masson模型预测焊点寿命。选取焊点钎料量、焊点高度、下焊盘直径作为影响焊点寿命的主要因素进行了3因素3水平正交实验,通过均值响应分析得到了影响凸点寿命的最敏感因素及最优形态尺寸组合。结果表明对焊点寿命影响最大的因素为下焊盘半径,其次是钎料量,最后是焊点高度,且上下等大的焊盘具有较好的可靠性。

The Immunity of Evolvable Digital Circuits to ESD Interference

With the rapid development of semiconductor technology and the increasing proliferation of emission sources, digital circuits are frequently used in harsh and hostile electromagnetic environments. Electrostatic Discharge （ESD） interferences are gradually gaining prominence, resulting in performance degradations, malfunctions and disturbances in component and/or system level applications. Conventional solutions to such problems are shielding, filtering and grounding. This paper proposes a novel Evolvable Digital Circuit （EDC） for intrinsic immunity. The key idea is motivated by the noise-robustness and fault-tolerance of the biological system. First, the architecture of the EDC is designed based on the cell structure. Then, ESD immunity tests are carried out on the most fragile element of the EDC in operation. Based on the results, fault models are also presented to simulate different functional disturbances. Finally, the immunity of the EDC is evaluated while it is exposed to a variety of simulated environments. The results which demonstrate a graceful immunity to ESD interference are presented.

Fault self-repair strategy based on evolvable hardware and reparation balance technology

In the face of harsh natural environment applications such as earth-orbiting and deep space satellites, underwater sea vehicles, strong electromagnetic interference and temperature stress,the circuits faults appear easily. Circuit faults will inevitably lead to serious losses of availability or impeded mission success without self-repair over the mission duration. Traditional fault-repair methods based on redundant fault-tolerant technique are straightforward to implement, yet their area, power and weight cost can be excessive. Moreover they utilize all plug-in or component level circuits to realize redundant backup, such that their applicability is limited. Hence, a novel selfrepair technology based on evolvable hardware（EHW） and reparation balance technology（RBT） is proposed. Its cost is low, and fault self-repair of various circuits and devices can be realized through dynamic configuration. Making full use of the fault signals, correcting circuit can be found through EHW technique to realize the balance and compensation of the fault output-signals. In this paper, the self-repair model was analyzed which based on EHW and RBT technique, the specific self-repair strategy was studied, the corresponding self-repair circuit fault system was designed, and the typical faults were simulated and analyzed which combined with the actual electronic devices. Simulation results demonstrated that the proposed fault self-repair strategy was feasible. Compared to traditional techniques, fault self-repair based on EHW consumes fewer hardware resources, and the scope of fault self-repair was expanded significantly.

A Novel Self-adaptive Circuit Design Technique Based on Evolvable Hardware

Since traditional fault tolerance methods of electronic systems are based on redundant fault tolerance technique,and their structures are fixed when circuits are designed,the self-adaptive ability is limited.In order to solve these problems,a novel circuit self-adaptive design technique based on evolvable hardware(EHW)is proposed.It features robustness,self-organization and self-adaption.It can be adapted to a complex environment through dynamic configuration of the circuit.In this paper,the proposed technique simulated.The consumption of hardware resources and the number of convergence iterations researched.The effectiveness and superiority of the proposed technique are verified.The designed circuit has the ability of resistible redundant-state interference(RRSI).The proposed technique has a broad application prospect,and it has great significance.

Co-pyrolysis of Sewage Sludge with Distillation Residue: Kinetics Analysis via Iso-conversional Methods

This study explored the synergistic interaction of sewage sludge(SS)and distillation residue(DR)during co-pyrolysis for the optimized treatment of sewage sludge in cement kiln systems,utilizing thermogravimetric analysis(TGA)and thermogravimetric analysis with mass spectrometry(TGA-MS).The results reveal the coexisting synergistic and antagonistic effects in the co-pyrolysis of SS/DR.The synergistic effect arises from hydrogen free radicals in SS and catalytic components in ash fractions,while the antagonistic effect is mainly due to the melting of DR on the surface of SS particles during pyrolysis and the reaction of SS ash with alkali metals to form inert substances.SS/DR co-pyrolysis reduces the yielding of coke and gas while increasing tar production.This study will promote the reduction,recycling,and harmless treatment of hazardous solid waste.

Role of fullerenols derivative 3HFWC in the treatment of Alzheimer's disease

Fullerenes:The extensive development of nanoscience that has marked this century continues to evolve,producing new materials,structures,and devices for the treatments of diverse pathologies.Fullerenes are a family of nanoparticles with great applicative promise due to their small size(approximately 1 nm in diameter),structure,and capacity to cross biological barriers.

Co-pyrolysis of Sewage Sludge with Paint Sludge: Kinetics and Thermodynamic Analysis via Iso-conversional Methods

This study explored the synergistic interaction of sewage sludge(SS)and automotive paint sludge(PS)during co-pyrolysis for the optimized treatment of sewage sludge in cement kiln systems,utilizing thermogravimetric analysis(TGA)and thermogravimetric-mass spectrometry(TGA-MS).The result reveals the coexisting synergistic and antagonistic effects in the co-pyrolysis of SS/PS.The synergistic effect arises from hydrogen free radicals in SS and catalytic components in PS,while the main source of the antagonistic effect is that,during the mechanical mixing process,the SS/PS is converted from the particulate form into a dough-like rubbery which contributes to the film-forming effect,hindering the volatilization of volatile components.SS/PS co-pyrolysis reduces the yielding of tar production while increasing coke and gas.This study will provide some in-depth insights into the co-pyrolysis of SS/PS,and offer theoretical support for the subsequent research on the collaborative disposal processes in cement kilns.

Ultrathin Limit on the Anisotropic Superconductivity of Single-Layered Cuprate Films

Exploring dimensionality effects on cuprates is important for understanding the nature of high-temperature superconductivity.By atomically layer-by-layer growth with oxide molecular beam epitaxy,we demonstrate that La_(2−x)Sr_(x)CuO_(4)(x=0.15)thin films remain superconducting down to 2 unit cells of thickness but quickly reach the maximum superconducting transition temperature at and above 4 unit cells.By fitting the critical magnetic field(μ0H_(c2)),we show that the anisotropy of the film’s superconductivity increases with decreasing film thickness,indicating that the superconductivity of the film gradually evolves from weak three-to two-dimensional character.These results are helpful to gain more insight into the nature of high-temperature superconductivity with dimensionality.

Genetic mechanism of body size variation in groupers:Insights from phylotranscriptomics

Animal body size variation is of particular interest in evolutionary biology,but the genetic basis remains largely unknown.Previous studies have shown the presence of two parallel evolutionary genetic clusters within the fish genus Epinephelus with evident divergence in body size,providing an excellent opportunity to investigate the genetic basis of body size variation in vertebrates.Herein,we performed phylotranscriptomic analysis and reconstructed the phylogeny of 13 epinephelids originating from the South China Sea.Two genetic clades with an estimated divergence time of approximately 15.4 million years ago were correlated with large and small body size,respectively.A total of 180 rapidly evolving genes and two positively selected genes were identified between the two groups.Functional enrichment analyses of these candidate genes revealed distinct enrichment categories between the two groups.These pathways and genes may play important roles in body size variation in groupers through complex regulatory networks.Based on our results,we speculate that the ancestors of the two divergent groups of groupers may have adapted to different environments through habitat selection,leading to genetic variations in metabolic patterns,organ development,and lifespan,resulting in body size divergence between the two locally adapted populations.These findings provide important insights into the genetic mechanisms underlying body size variation in groupers and species differentiation.

Spatial-temporal distribution and geochemistry of highly evolved Mesozoic granites in Great Xing’an Range,NE China:Discriminant criteria and geological significance

Highly evolved granite is an important sign of the mature continent crust and closely associated with deposits of rare metals.In this work,the authors undertake systematically zircon U-Pb ages and whole rock elemental data for highly evolved granitic intrusions from the Great Xing’an Range(GXR),NE China,to elucidate their discriminant criteria,spatial-temporal distribution,differentiation and geodynamic mecha-nism.Geochemical data of these highly evolved granites suggest that high w(SiO_(2))(>70%)and differentiation index(DI>88)could be quantified indicators,while strong Eu depletion,high TE_(1,3),lowΣREE and low Zr/Hf,Nb/Ta,K/Rb could only be qualitative indicators.Zircon U-Pb ages suggest that the highly evolved gran-ites in the GXR were mainly formed in Late Mesozoic,which can be divided into two major stages:Late Ju-rassic-early Early Cretaceous(162-136 Ma,peak at 138 Ma),and late Early Cretaceous(136-106 Ma,peak at 126 Ma).The highly evolved granites are mainly distributed in the central-southern GXR,and display a weakly trend of getting younger from northwest to southeast,meanwhile indicating the metallogenic potential of rare metals within the central GXR.The spatial-temporal distribution,combined with regional geological data,indicates the highly evolved Mesozoic granites in the GXR were emplaced in an extensional environ-ment,of which the Late Jurassic-early Early Cretaceous extension was related to the closure of the Mongol-Okhotsk Ocean and roll-back of the Paleo-Pacific Plate,while the late Early Cretaceous extension was mainly related to the roll-back of the Paleo-Pacific Plate.

Closer Trade Ties:An Engine for Economic Growth

The origins of Malaysia-China ties can be traced back to ancient trade of goods.Throughout history,the bilateral relationship has endured ebbs and flows to evolve into full-fledged diplomatic and economic interactions.This evolution reflects changes in Southeast Asian and global landscapes,which have been heavily influenced by post-World War II realignment,Cold War politics,and the rise of China.

Evolvable dialogue state tracking for statistical dialogue management

Statistical dialogue management is the core of cognitive spoken dialogue systems （SDS） and has attracted great research interest. In recent years, SDS with the ability of evolution is of particular interest and becomes the cuttingedge of SDS research. Dialogue state tracking （DST） is a process to estimate the distribution of the dialogue states at each dialogue turn, given the previous interaction history. It plays an important role in statistical dialogue management. To provide a common testbed for advancing the research of DST, international DST challenges （DSTC） have been organised and well-attended by major SDS groups in the world. This paper reviews recent progresses on rule-based and statistical approaches during the challenges. In particular, this paper is focused on evolvable DST approaches for dialogue domain extension. The two primary aspects for evolution, semantic parsing and tracker, are discussed. Semantic enhancement and a DST framework which bridges rule-based and statistical models are introduced in detail. By effectively incorporating prior knowledge of dialogue state transition and the ability of being data-driven, the new framework supports reliable domain extension with little data and can continuously improve with more data available. This makes it excellent candidate for DST evolution. Experiments show that the evolvable DST approaches can achieve the state-of-the-art performance and outperform all previously submitted trackers in the third DSTC.

An Improved Evolvable Oscillator and Basis Function Set for Control of an Insect-Scale Flapping-Wing Micro Air Vehicle

This paper introduces an improved evolvable and adaptive hardware oscillator design capable of supporting adaptation intended to restore control precision in damaged or imperfectly manufactured insect-scale flapping-wing micro air vehicles. It will also present preliminary experimental results demonstrating that previously used basis function sets may have been too large and that significantly improved learning times may be achieved by judiciously culling the oscillator search space. The paper will conclude with a discussion of the application of this adaptive, evolvable oscillator to full vehicle control as well as the consideration of longer term goals and requirements.

英国高中地理教材栏目设置的特点及启示——以Geography B Evolving Planet为例

以英国中学地理教材Geography B Evolving Planet中的教材栏目为研究对象,结合其在教材中实际发挥的功能,将八种主要的教材栏目划分为问题思考类、技能训练类、信息提示类和考试导向类四大类。这四大类教材栏目体现出了不同的特点。问题思考类栏目指向不同教学目标,技能训练类栏目凸显实用性和应用性的学科特色,信息提示类栏目关注学生心理特点,考试导向类栏目提高应试答题技巧。受此启发,未来我国中学地理教材栏目设置应有所侧重,即教材栏目在内容设置上要注重针对性,在形式设置上要增加多样性,在外观设置上要注重醒目性。

Editorial:Driving into Future with Reliable,Secure,Efficient and Intelligent MetaVehicles

Welcome to the sixth issue of the IEEE/CAA Journal of Automatica Sinica(JAS)in 2023!In the first issue in 2023,I briefly discussed about MetaVehicles,a technological expression of intelligent vehicles,robotics,AI,blockchain,knowledge automation,networking and communication[1].As the concept of the Metaverse continues to evolve and expand,the range of vehicle entities is diversely enlarged,including passenger vehicles,heavy duty vehicles,rail vehicles,marine vehicles,aerial vehicles,and other types of transportation.The development and use of MetaVehicles are likely to become more sophisticated.Therefore,from a systems and control perspective,new methods of control,estimation and optimization should be developed to achieve the improved vehicular control system stability and reliability in the physical space.

Subspace Clustering in High-Dimensional Data Streams:A Systematic Literature Review

Clustering high dimensional data is challenging as data dimensionality increases the distance between data points,resulting in sparse regions that degrade clustering performance.Subspace clustering is a common approach for processing high-dimensional data by finding relevant features for each cluster in the data space.Subspace clustering methods extend traditional clustering to account for the constraints imposed by data streams.Data streams are not only high-dimensional,but also unbounded and evolving.This necessitates the development of subspace clustering algorithms that can handle high dimensionality and adapt to the unique characteristics of data streams.Although many articles have contributed to the literature review on data stream clustering,there is currently no specific review on subspace clustering algorithms in high-dimensional data streams.Therefore,this article aims to systematically review the existing literature on subspace clustering of data streams in high-dimensional streaming environments.The review follows a systematic methodological approach and includes 18 articles for the final analysis.The analysis focused on two research questions related to the general clustering process and dealing with the unbounded and evolving characteristics of data streams.The main findings relate to six elements:clustering process,cluster search,subspace search,synopsis structure,cluster maintenance,and evaluation measures.Most algorithms use a two-phase clustering approach consisting of an initialization stage,a refinement stage,a cluster maintenance stage,and a final clustering stage.The density-based top-down subspace clustering approach is more widely used than the others because it is able to distinguish true clusters and outliers using projected microclusters.Most algorithms implicitly adapt to the evolving nature of the data stream by using a time fading function that is sensitive to outliers.Future work can focus on the clustering framework,parameter optimization,subspace search techniques,memory-efficient synopsis structures,explicit cluster change detection,and intrinsic performance metrics.This article can serve as a guide for researchers interested in high-dimensional subspace clustering methods for data streams.