Artificial intelligence in cyber security: research advances,challenges, and opportunities

Artificial Intelligence Review - In recent times, there have been attempts to leverage artificial intelligence (AI) techniques in a broad range of cyber security applications. Therefore, this paper...     

A tight coupling mapping method to integrate the ESKF,g2o,and point cloud alignment

The Journal of Supercomputing - High-precision point cloud maps have drawn increasing attention due to their wide range of applications. In recent decades, point cloud maps are normally generated...     

室内场景下应用拓扑结构的高效路径规划算法

针对基于随机采样的路径规划算法效率低且采样具有随机性的问题,提出一种应用拓扑结构的高效路径规划算法ATIRRT^*。通过引入拓扑节点代替STIRRT*算法中Harris角点检测算法得到的特征点进行采样,给出基于阈值的自适应选择方法来消除路径骨架上提取的冗余特征点,利用该阈值得到的拓扑节点可以使随机树的扩展更具方向性,从而减少寻找初始路径的时间和代价。根据非单一父节点的连接方式加强交叉支路上的拓扑节点间的联系,通过节点扩充策略增加相邻拓扑节点间的节点数量以加快优化算法的收敛。在此基础上定义相关约束条件将初始路径分段并进行逐段优化,以提高优化算法的效率。在常规环境、狭长空间和仿真的室内环境3种类型地图上的仿真结果表明,相较于STIRRT^*算法,改进算法在规划路径长度上平均减少8%,在规划时间上平均降低10%,可快速地找到更优的初始路径,同时在优化过程中减少了无用的探索空间,提高了搜索效率。     

旋转超声磨削钛合金有限元仿真与试验研究

为了研究固结磨粒磨具的磨料粒度对旋转超声磨削钛合金磨削力的影响,采用随机空间平面切割正六面体的方法构建了具有实际磨粒几何特征的不规则多面体磨粒,并基于虚拟格子法建立了磨粒在磨具端面随机分布的多颗磨粒磨具模型。使用Deform-3D软件构建了三维旋转超声磨削钛合金有限元模型,采用拉格朗日增量算法获得了多颗磨粒磨具旋转超声磨削钛合金Ti6Al4V的磨削力仿真值,得到了磨料粒度对磨削力的影响规律,并通过试验进行了验证。结果表明,旋转超声磨削钛合金磨削力随着磨料粒度的增大而减小,且试验结果和仿真结果具有一致性,说明了多颗磨粒磨具模型、旋转超声磨削有限元模型具有一定的准确性,为多颗磨粒磨具旋转超声磨削的相关研究提供了新的方法。     

我国再制造产业及其发展战略

再制造是制造业产业链的延伸,属于先进制造和绿色制造的范畴,《中国制造2025》提出要"大力发展再制造产业,实施高端再制造、智能再制造、在役再制造"。当前,我国再制造试点企业数量和再制造产品种类不断增加,再制造政策法规、基础理论、关键技术、行业标准得到不断创新完善。未来,再制造工程将向"绿色、优质、高效、智能、服务"五大方向发展,重点突破若干再制造核心关键技术,完善多个支撑体系,形成一批再制造领军产业。     

Self-organizing maps for pattern recognition in design of alloys

A combined experimental–computational methodology for accelerated design of AlNiCo-type permanent magnetic alloys is presented with the objective of simultaneously extremizing several magnetic properties. Chemical concentrations of eight alloying elements were initially generated using a quasi-random number generator so as to achieve a uniform distribution in the design variable space. It was followed by manufacture and experimental evaluation of these alloys using an identical thermo-magnetic protocol. These experimental data were used to develop meta-models capable of directly relating the chemical composition with desired macroscopic properties of the alloys. These properties were simultaneously optimized to predict chemical compositions that result in improvement of properties. These data were further utilized to discover various correlations within the experimental dataset by using several concepts of artificial intelligence. In this work, an unsupervised neural network known as self-organizing maps was used to discover various patterns reported in the literature. These maps were also used to screen the composition of the next set of alloys to be manufactured and tested in the next iterative cycle. Several of these Pareto-optimized predictions out-performed the initial batch of alloys. This approach helps significantly reducing the time and the number of alloys needed in the alloy development process.     

A Metal–Polyphenol Network Coated Nanotheranostic System for Metastatic Tumor Treatments

As a characteristic trait of most tumor types, metastasis is the major cause of the death of patients. In this study, a photothermal agent based on gold nanorod is coated with metal (Gd³⁺)‐organic (polyphenol) network to realize combination therapy for metastatic tumors. This nanotheranostic system significantly enhances antitumor therapeutic effects in vitro and in vivo with the combination of photothermal therapy (PTT) and chemotherapy, also can remarkably prevent the invasion and metastasis due to the presence of polyphenol. After the treatment, an 81% decrease in primary tumor volumes and a 58% decrease in lung metastasis are observed. In addition, the good performance in magnetic resonance imaging, computerized tomography, and photothermal imaging of the nanotheranostic system can realize image‐guided therapy. The multifunctional nanotheranostic system will find a great potential in diagnosis and treatment integration in tumor treatments, and broaden the applications of PTT treatment.     

Design of active and stable oxygen reduction reaction catalysts by embedding Co<Subscript><Emphasis Type="Italic">x</Emphasis></Subscript>O<Subscript><Emphasis Type="Italic">y</Emphasis></Subscript> nanoparticles into nitrogen-doped carbon

The oxygen reduction reaction (ORR) is essential in research pertaining to life science and energy. In applications, platinum-based catalysts give ideal reactivity, but, in practice, are often subject to high costs and poor stability. Some cost-efficient transition metal oxides have exhibited excellent ORR reactivity, but the stability and durability of such alternative catalyst materials pose serious challenges. Here, we present a facile method to fabricate uniform Co _x O _y nanoparticles and embed them into N-doped carbon, which results in a composite of extraordinary stability and durability, while maintaining its high reactivity. The half-wave potential shows a negative shift of only 21 mV after 10,000 cycles, only one third of that observed for Pt/C (63 mV). Furthermore, after 100,000 s testing at a constant potential, the current decreases by only 17%, significantly less than for Pt/C (35%). The exceptional stability and durability results from the system architecture, which comprises a thin carbon shell that prevents agglomeration of the Co _x O _y nanoparticles and their detaching from the substrate.

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A series of nanoparticles with phase-separated structures by 1,1-diphenylethene controlled one-step soap-free emulsion copolymerization and their application in drug release

A facile one-step approach to synthesize various phase-separated porous, raspberry-like, flower-like, core–shell and anomalous nanoparticles and nanocapsules via 1,1-diphenylethene (DPE) controlled soap-free emulsion copolymerization of styrene (S) with glycidyl methacrylate (GMA), or acrylic acid (AA) is reported. By regulating the mass ratio of S/GMA, transparent polymer solution, porous and anomalous P(S-GMA) particles could be produced. The P(S-GMA) particles turn from flower-like to raspberry-like and then to anomalous structures with smooth surface as the increase of divinylbenzene (DVB) crosslinker. Transparent polymer solution, nanocapsules and core–shell P(S-AA) particles could be obtained by altering the mole ratio of S/AA; anomalous and raspberry-like P(S-AA) particles are produced by adding DVB. The unpolymerized S resulted from the low monomer conversion in the presence of DPE aggregates to form nano-sized droplets, and migrates towards the external surfaces of the GMA-enriched P(S-GMA) particles and the internal bulk of the AA-enriched P(S-AA) particles. The nano-sized droplets function as in situ porogen, porous P(S-GMA) particles and P(S-AA) nanocapsules are produced when the porogen is removed. This novel, facile, one-step method with excellent controllability and reproducibility will inspire new strategies for creating hierarchical phase-separated polymeric particles with various structures by simply altering the species and ratio of comonomers. The drug loading and release experiments on the porous particles and nanocapsules demonstrate that the release of doxorubicin hydrochloride is very slow in weakly basic environment and quick in weakly acidic environment, which enables the porous particles and nanocapsules with promising potential in drug delivery applications.

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