Deep Learning(DL)has revolutionized the field of Artificial Intelligence(Al)in various domains such as computer vision(CV)and natural language processing.However,DL models have limitations including the need for large...Deep Learning(DL)has revolutionized the field of Artificial Intelligence(Al)in various domains such as computer vision(CV)and natural language processing.However,DL models have limitations including the need for large labeled datasets,lack of interpretability and explainability,potential bias and fairness issues,and limitations in common sense reasoning and contextual understanding.On the other side,DL has shown significant potential in construction for safety and quality inspection tasks using CV models.However,current CV approaches may lack spatial context and measurement capabilities,and struggle with complex safety and quality requirements.The integration of Neuro-Symbolic Computing(NSC),an emerging field that combines DL and symbolic reasoning,has been proposed as a potential solution to address these limitations.NSC has the potential to enable more robust,interpretable,and accurate AI systems in construction by harnessing the strengths of DL and symbolic reasoning.The combination of symbolism and connectionism in NSC can lead to more efficient data usage,improved generalization ability,and enhanced interpretability.Further research and experimentation are needed to effectively integrate NSC with large models and advance CV technologies for precise reporting of safety and quality inspection results in construction.展开更多
高等桥梁结构理论课程一直是桥梁工程专业研究生的必修课程,也是针对留学生开放的专业课程。从2017—2018学年第一学期开始全英文授课,面向国际学生以及选择英文学习的国内学生。高等桥梁结构理论的英文版教材Advanced Theory of Bridge...高等桥梁结构理论课程一直是桥梁工程专业研究生的必修课程,也是针对留学生开放的专业课程。从2017—2018学年第一学期开始全英文授课,面向国际学生以及选择英文学习的国内学生。高等桥梁结构理论的英文版教材Advanced Theory of Bridge Structures是在中文版基础上内容适当取舍,主干内容不变,并结合教学课时和教学实践编写的全英文教材。该文首先介绍原中文版课程及教材背景,重点对英文版教材的编写思路、目录编排、选材内容特点等进行较为详细的叙述。同时,经过几年的英文版教学实践,该文也介绍英文版教学在课程建设和学生能力提升等方面的进展情况。展开更多
In the tobacco industry,insider employee attack is a thorny problem that is difficult to detect.To solve this issue,this paper proposes an insider threat detection method based on heterogeneous graph embedding.First,t...In the tobacco industry,insider employee attack is a thorny problem that is difficult to detect.To solve this issue,this paper proposes an insider threat detection method based on heterogeneous graph embedding.First,the interrelationships between logs are fully considered,and log entries are converted into heterogeneous graphs based on these relationships.Second,the heterogeneous graph embedding is adopted and each log entry is represented as a low-dimensional feature vector.Then,normal logs and malicious logs are classified into different clusters by clustering algorithm to identify malicious logs.Finally,the effectiveness and superiority of the method is verified through experiments on the CERT dataset.The experimental results show that this method has better performance compared to some baseline methods.展开更多
The 2024 Government Work Report proposes to promote the development and utilization of distributed energy.This marks the inaugural inclusion of“distributed energy”in the Government Work Report.In constructing China...The 2024 Government Work Report proposes to promote the development and utilization of distributed energy.This marks the inaugural inclusion of“distributed energy”in the Government Work Report.In constructing China’s new energy system,distributed energy stands to encounter substantial growth prospects and urgently requires addressing industry challenges and enhancing the market ecosystem for its advancement.展开更多
文摘Deep Learning(DL)has revolutionized the field of Artificial Intelligence(Al)in various domains such as computer vision(CV)and natural language processing.However,DL models have limitations including the need for large labeled datasets,lack of interpretability and explainability,potential bias and fairness issues,and limitations in common sense reasoning and contextual understanding.On the other side,DL has shown significant potential in construction for safety and quality inspection tasks using CV models.However,current CV approaches may lack spatial context and measurement capabilities,and struggle with complex safety and quality requirements.The integration of Neuro-Symbolic Computing(NSC),an emerging field that combines DL and symbolic reasoning,has been proposed as a potential solution to address these limitations.NSC has the potential to enable more robust,interpretable,and accurate AI systems in construction by harnessing the strengths of DL and symbolic reasoning.The combination of symbolism and connectionism in NSC can lead to more efficient data usage,improved generalization ability,and enhanced interpretability.Further research and experimentation are needed to effectively integrate NSC with large models and advance CV technologies for precise reporting of safety and quality inspection results in construction.
基金国家自然科学基金“网格配筋混凝土结构抗剪机理研究”(51178335)2021年同济大学研究生教育研究与改革建设项目“Advanced Theory of Bridge Structures”(2021JC05)。
文摘高等桥梁结构理论课程一直是桥梁工程专业研究生的必修课程,也是针对留学生开放的专业课程。从2017—2018学年第一学期开始全英文授课,面向国际学生以及选择英文学习的国内学生。高等桥梁结构理论的英文版教材Advanced Theory of Bridge Structures是在中文版基础上内容适当取舍,主干内容不变,并结合教学课时和教学实践编写的全英文教材。该文首先介绍原中文版课程及教材背景,重点对英文版教材的编写思路、目录编排、选材内容特点等进行较为详细的叙述。同时,经过几年的英文版教学实践,该文也介绍英文版教学在课程建设和学生能力提升等方面的进展情况。
基金Supported by the National Natural Science Foundation of China(No.62203390)the Science and Technology Project of China TobaccoZhejiang Industrial Co.,Ltd(No.ZJZY2022E004)。
文摘In the tobacco industry,insider employee attack is a thorny problem that is difficult to detect.To solve this issue,this paper proposes an insider threat detection method based on heterogeneous graph embedding.First,the interrelationships between logs are fully considered,and log entries are converted into heterogeneous graphs based on these relationships.Second,the heterogeneous graph embedding is adopted and each log entry is represented as a low-dimensional feature vector.Then,normal logs and malicious logs are classified into different clusters by clustering algorithm to identify malicious logs.Finally,the effectiveness and superiority of the method is verified through experiments on the CERT dataset.The experimental results show that this method has better performance compared to some baseline methods.
文摘The 2024 Government Work Report proposes to promote the development and utilization of distributed energy.This marks the inaugural inclusion of“distributed energy”in the Government Work Report.In constructing China’s new energy system,distributed energy stands to encounter substantial growth prospects and urgently requires addressing industry challenges and enhancing the market ecosystem for its advancement.
