In the dynamic field of robotics engineering, nanorobot technology has witnessed rapid advancements. Developing a technology roadmap is essential for quickly identifying the trends and key technological aspects of nanorobotics from an array of multi-source data. Traditional research methods, such as Delphi surveys, bibliometrics, patent analysis, and patent paper citation analyses, often fail to capture the rich semantic information available. Moreover, these approaches generally provide a unidimensional perspective, which restricts their capacity to depict the complex nature of technological evolution. To overcome these shortcomings, this paper introduces a novel framework that utilizes the ALBERT method combined with multi-source data for critical theme extraction. It integrates varied data sources, including academic papers and patents, to explore the interrelation within the nanorobot technology roadmap. The methodology begins with text feature extraction, clustering algorithms, and theme mining to identify dominant technological themes. Subsequently, it applies semantic similarity measures to connect multiple themes, employing a “multi-layer ThemeRiver map” for a visual representation of these inter-layer connections. The paper concludes with a comprehensive analysis from both the technological research and industrial application perspectives, underscoring the principal developmental themes and insights of nanorobot technology, and projecting its future directions.

Optimizing arc welding parameters is of great significance for improving welding quality and controlling welding costs. BP neural network is a relatively mature and widely used network, a parameter prediction model based on BP neural network is proposed and established, the training process adopts the gradient descent BP algorithm, set model learning rate to 0.05, target accuracy to 1 × 10–4, and training step to 30000. Considering the strong correlation between welding parameters, and the line energy is introduced to judge the prediction accuracy of the model, and the accuracy of welding parameters predicted by the overall model is above 90

The integrated design of middle and higher education is one of the important tasks in building a modern vocational education system. The catalog of vocational education majors（2021 edition） fully embodies the requirements of vertical integration of middle and higher education levels, as well as the vertical connection of major systems. Many vocational schools are actively exploring talent training reforms that combine the needs of local industrial development. This paper takes the intelligent manufacturing major group as an example to conduct cluster analysis on multi-level job groups in this field. It generates a list of capability requirements and integrates expert interactive to optimize the results. The paper then proposes a hierarchically linked core course list and training practice system. This integrated design method is based on job big data analysis, which has certain reference value for the integrated construction of middle and higher education and the promotion of the integration of production and education.

[目的/意义]提出一种基于文档向量化和自动化短语挖掘的改进主题建模方法(Doc2Vec-KMeans++-TopMine,DKT),从多维视角识别领域内的技术演化路径,展示领域内技术的发展与现状.[方法/过程]获取研究领域内的论文、专利、产品等多源数据,综合采用文档向量化、聚类算法和短语挖掘算法,完成领域多源数据的融合主题挖掘,通过语义相似度计算进行多源融合主题的关联与演化路径的识别,采用"主题河流图"可视化方法绘制多维度技术演化路径,从前沿研究、技术研发、市场应用等多维度视角出发开展领域演化分析.[结果/结论]选取数控机床领域进行实证研究,实验结果表明,利用DKT方法挖掘到的演化路径信息丰富,可以进行多维技术演化路径分析,并证明了其有效性,同时还得到了多个维度视角下的领域发展过程,发现了数控机床领域的3种技术演化模式.

众多职业院校正在探索智能制造导论课程开设的可行性与方法.通过分析综合类或理工类职业院校在全校开设智能制造导论课的必要性,通过与智能制造技术的相关性分析确定了本课程在强相关专业的专业领域基础课,弱相关专业的校级通识课的课程定位与目标.通过智能制造技术体系分析和典型教材分析完成了智能制造导论的课程内容和实践教学设计.

目前许多院校通过相关专业升级或开设智能制造工程等新专业来为智能制造领域输送人才.由于智能制造领域产教融合资源缺乏等原因,院校在开设新专业或专业升级时难以加强专业课程体系与产业的相关性.本文基于2021年人社部颁布的《智能制造工程技术人员国家职业技术技能标准》(简称《标准》),构建了智能制造领域相关专业的专业课程体系评价模型,并对9个相关专业的专业课程体系进行了智能制造相关性评价,从评价指标的角度为专业课程体系提供建议;同时本文基于该模型开发了高职本科智能制造工程技术和高职专科智能制造装备技术等新专业的专业课程体系原型,以供院校开发新专业参考.

针对目前数字孪生车间构建中工业机器人等虚拟实体建模复杂、开发周期长等问题,提出了一种数字孪生车间工业机器人虚实驱动系统的模块化构建方法,即将虚实驱动系统分为设置模型参数的交互层和按功能需求设计配置的控制层,然后将实体工业机器人等抽象为单功能原子模型耦合而成的仿真模型.模块化分层构建虚实驱动系统的方法能快速有效地实现工业机器人等数字孪生虚拟实体的建模,以及工业机器人在虚拟空间中的仿真运行模拟和虚实同步运行.

In recent years, nanogenerator technology has developed rapidly with the rise of cloud computing, artificial intelligence, and other fields. Therefore, the quick identification of the evolutionary path of nanogenerator technology from a large amount of data attracts much attention. It is of great significance in grasping technical trends and analyzing technical areas of interest. However, there are some limitations in previous studies. On the one hand, previous research on technological evolution has generally utilized bibliometrics, patent analysis, and citations between patents and papers, ignoring the rich semantic information contained therein; on the other hand, its evolution analysis perspective is single, and it is difficult to obtain accurate results. Therefore, this paper proposes a new framework based on the methods of Sentence-BERT and phrase mining, using multi-source data, such as papers and patents, to unveil the evolutionary path of nanogenerator technology. Firstly, using text vectorization, clustering algorithms, and the phrase mining method, current technical themes of significant interest to researchers can be obtained. Next, this paper correlates the multi-source fusion themes through semantic similarity calculation and demonstrates the multi-dimensional technology evolutionary path by using the “theme river map”. Finally, this paper presents an evolution analysis from the perspective of frontier research and technology research, so as to discover the development focus of nanogenerators and predict the future application prospects of nanogenerator technology.

目前在识别中外中高档数控机床技术差距的研究中,存在技术缺口信息不够丰富、缺乏基于数据层面对技术缺口内容进行客观描述等问题.基于文献计量与专利分析及信息可视化工具,使用多源数据分析全球数控机床领域研究进展与趋势,通过国内外典型企业的产品数据与专利信息匹配来识别中国中高档数控机床技术缺口与短板,为相关决策提供数据和方法支持.研究结果表明:中国在中高档数控机床的主机产品、可靠性技术、数字化设计技术等方面仍存在不同层次的创新缺口.基于分析结果,对中国中高档数控机床的创新发展,分别从国家、企业和科研机构层面提出加强基础共性技术研发、构筑起能与工业发达国家竞争的技术创新体系和技术创新人才队伍,突破关键主机及成套装备创新、加强工艺研究和引进消化吸收力度以及相应的创新平台建设,加强情报智力支持作用、注重人才培养并积极为政府和企业提供动态性咨询服务等对策建议.

虚拟实体是数字孪生五维模型中重要的组成部分,其行为模型描述了物理实体在外部环境与内部运行机制作用下的实时响应及行为.针对离散制造车间数字孪生虚拟实体行为模型缺乏统一描述与精确定义的难题,提出一种使用基于值的离散事件系统规范(VDEVS)对行为模型进行描述的方法.在原有数字孪生五维模型基础上定义了数字孪生车间虚拟实体分层模型,实现了其与数字孪生车间物理实体的一一映射.通过对传统离散事件系统仿真规范(DEVS)进行扩展提出了VDEVS,从而更加精确地描述离散制造车间复杂系统级、系统级、单元级虚拟实体的行为.最后,针对某加工单元,利用基于VDEVS的方法对其行为模型进行了描述.

Identifying the evolution path of a research field is essential to scientific and technological innovation. There have been many attempts to identify the technology evolution path based on the topic model or social networks analysis, but many of them had deficiencies in methodology. First, many studies have only considered a single type of information (text or citation information) in scientific literature, which may lead to incomplete technology path mapping. Second, the number of topics in each period cannot be determined automatically, making dynamic topic tracking difficult. Third, data mining methods fail to be effectively combined with visual analysis, which will affect the efficiency and flexibility of mapping. In this study, we developed a method for mapping the technology evolution path using a novel non-parametric topic model, the citation involved Hierarchical Dirichlet Process (CIHDP), to achieve better topic detection and tracking of scientific literature. To better present and analyze the path, D3.js is used to visualize the splitting and fusion of the evolutionary path. We used this novel model to mapping the artificial intelligence research domain, through a successful mapping of the evolution path, the proposed method’s validity and merits are shown. After incorporating the citation information, we found that the CIHDP can be mapping a complete path evolution process and had better performance than the Hierarchical Dirichlet Process and LDA. This method can be helpful for understanding and analyzing the development of technical topics. Moreover, it can be well used to map the science or technology of the innovation ecosystem. It may also arouse the interest of technology evolution path researchers or policymakers.

[目的/意义]特征提取会很大程度地影响分类效果,而传统TF-IDF特征提取方法缺乏对特征词上下文环境和对特征词在类之间分布状况的考虑.[方法/过程]本文提出一种改进TF-IDF特征提取的方法:①基于文本网络和改进PageRank算法计算节点重要程度值,解决传统TF-IDF忽略文本结构信息的问题;②增加特征值IDF值的方差来衡量特征词w在不同类别文本集中程度的分布情况,解决传统TF-IDF忽略特征词在类之间分布状况的不足.[结果/结论]基于该改进方法构建了文本分类模型,对3D打印数据进行分类实验.对比算法改进前后的分类效果,验证了该方法能够有效提高文本特征词提取的准确度.

This study uses bibliometrics,topic modeling,and social network analysis to conduct a comprehensive literature review.The aim is to provide a systematic and objective analysis of the quantitative methods in the technology foresight;it also tries to identify the quantitative foresight methods and the research questions on technology foresight and their evolutionary trends.It is found that the exploratory method is still the dominant approach for predicting the future development,which is limited to the path-dependent progressive innovation.Recently,studies use combined methods based on data mining that can identify the future uncertainty oriented disruptive technology and its path transition,which has become an emerging approach for technology foresight.

MicroRNAs miRNAs are involved in multiple biological processes, such as tumorigenesis and differentiation. The functions of most miRNAs still remain elusive. Measuring functional similarity between miRNAs is an important step to predict the functions of novel miRNAs and further identify disease-related miRNAs. In this study, we applied a biomedical text-mining method to assess miRNA functional similarities. According to validations, miRNA functional similarities inferred from biomedical texts are reliable and have the potential to distinguish disease miRNA pairs from random ones. Therefore, we further applied this set of similarity scores to uncover disease-related miRNAs, and achieved a high AUC of 0.941. Compared with existing methods, our set of miRNA functional similarity scores has higher reliability, larger coverage, and superior performance in prioritising disease-related miRNAs. We also conducted the case studies examining four common diseases and found that majority of the top ten candidates have been validated by experimental evidence.

In the perspective of knowledge flow,the paper constructed a quantitative engineering technology forecasting model by combining the clustering and main path method,based on the litera-tures and patent data.Taking harmonic reducer as an example,the literatures and patent data of 1980~2009 were applied to make a engineering technology forecasting by the model,and compared the re-sults with the technologies during the 2010~2014.It turns out that the proposed framework is feasi-ble and effective.At last,the engineering technology trends were forecasted for the next five years as follows:all countries of the world will devote themselves to the areas of improving the precision, backlash,transmission efficiency,bearing capacity,reliability and other performance-related technol-ogies,miniaturization and light weight of transmission,as well as optimization of component parts.

人力资本专用性、合作过程中可信承诺以及投资外部性是影响企业参与现代学徒制职业教育的关键因素.西方代表性国家的学徒制主要是从理顺政府、行业协会、企业、学校关系人手,较好地克服了关键因素引起的冲突与挑战.佛山市以政府主导为稳定点、企业的积极参与为重难点来发展和完善现代学徒制,通过发展产权混合、资源共享、体制灵活的公共实训中心,以协议方式运营,有利于健全治理机构和决策机制,促进了现代学徒制新机制的构建.

The maximum number of a thread pool impacts the efficiency of thread. In the actual software design,software designers tend to rely on experience to set the maximum number of concurrent of a thread pool,resulting in the software design of the subjectivity and blindness. The network request file is setted an impact factor of maximum concurrency on the research target thread pool. Setting mod- eling analysis between the network request file and the maximum concurrency of thread pool,analysis show that the network request file is inversely proportional to the maximum concurrency of thread pool within a certain range,and optimizing the model. Proposing a meth- od that the maximum concurrency of thread pool is dynamically setted by the network request file,the research result is tested by multi- thread download model of IOS.

An optimized multi-objective mathematical model was built based on four different test paper properties. Then, an improved genetic algorithm was proposed to solve this mathematical problem. Three aspects of the genetic algorithm, including the gene encoding, gene modification, and probability of the genetic parameter were improved to avoid the disadvantages of premature convergence and slow-evolution. The simulation analysis of the experimental data indicates that the success rate is improved to 100% and the running time of algorithm is limited within 300 ms. So this mathematical model and the improved genetic algorithm promotes the running efficiency of the execution and evaluates and controls the quality of the generating result in the task of intelligent-generating test paper.

Some strains of avian influenza A virus (AIV) can directly transmit from their natural hosts to humans. These avian-to-human transmissions have continuously been reported to cause human deaths worldwide since 1997. Predicting whether AIV strains can transmit from avian to human is valuable for early warning of AIV strains with human pandemic potential. In this study, we constructed a computational model to predict avian-to-human transmission of AIV based on physicochemical properties. Initially, ninety signature positions in the inner protein sequences were extracted with the entropy method. These positions were then encoded with 531 physicochemical features. Subsequently, the optimal subset of these physicochemical features was mined with several feature selection methods. Finally, a support vector machine (SVM) model named A2H was established to integrate the selected optimal features. The experimental results of cross-validation and an independent test show that A2H has the capability of predicting transmission of AIV from avian to human.