Biblio

The development of artificial intelligence will certainly fundamentally change the pattern of human work. With the promotion of top-level strategies, vocational education can only develop sustainably by integrating with science and technology. Artificial intelligence is a branch of computer science that studies the basic theories, methods and techniques of how to apply computer hardware and software to simulate certain intelligent human behaviors. Artificial intelligence applied to vocational education mainly focuses on resource network technology and integrated distributed intelligent system, which organically integrates various different expert systems (ES), management information systems (MIS), intelligent networks, decision support systems (DSS), databases, numerical computing packages and graphics processing programs to solve complex problems. Artificial intelligence will certainly empower vocational education and give rise to a vocational education revolution. In the process of continuous improvement of AI, it is a more practical approach to apply various already mature AI technologies to vocational education practice. Establishing an intelligent vocational education ecology enables traditional education and AI to complement each other's advantages and jointly promote the healthy and sustainable development of vocational education ecology.

In the 21st century, integrated transport, service and mobility concepts for real-life situations enabled by automation system and smarter connectivity. These services and ideas can be blessed from cloud computing, and big data management techniques for the transport system. These methods could also include automation, security, and integration with other modes. Integrated transport system can offer new means of communication among vehicles. This paper presents how hybrid could computing influence to make urban transportation smarter besides considering issues like security and privacy. However, a simple structured framework based on a hybrid cloud computing system might prevent common existing issues.

The research question of this study is: How Integration Readiness Level (IRL) metrics can be understood and realized in the domain of border control information systems. The study address to the IRL metrics and their definition, criteria, references, and questionnaires for validation of border control information systems in case of the shared maritime situational awareness system. The target of study is in improvements of ways for acceptance, operational validation, risk assessment, and development of sharing mechanisms and integration of information systems and border control information interactions and collaboration concepts in Finnish national and European border control domains.
 

This paper presents an overview of the research project “High-Performance Hybrid Simulation/Measurement-Based Tools for Proactive Operator Decision-Support”, performed under the auspices of the U.S. Department of Energy grant DE-OE0000628. The objective of this project is to develop software tools to provide enhanced real-time situational awareness to support the decision making and system control actions of transmission operators. The integrated tool will combine high-performance dynamic simulation with synchrophasor measurement data to assess in real time system dynamic performance and operation security risk. The project includes: (i) The development of high-performance dynamic simulation software; (ii) the development of new computationally effective measurement-based tools to estimate operating margins of a power system in real time using measurement data from synchrophasors and SCADA; (iii) the development a hybrid framework integrating measurement-based and simulation-based approaches, and (iv) the use of cutting-edge visualization technology to display various system quantities and to visually process the results of the hybrid measurement-base/simulation-based security-assessment tool. Parallelization and high performance computing are utilized to enable ultrafast transient stability analysis that can be used in a real-time environment to quickly perform “what-if” simulations involving system dynamics phenomena. EPRI's Extended Transient Midterm Simulation Program (ETMSP) is modified and enhanced for this work. The contingency analysis is scaled for large-scale contingency analysis using MPI-based parallelization. Simulations of thousands of contingencies on a high performance computing machine are performed, and results show that parallelization over contingencies with MPI provides good scalability and computational gains. Different ways to reduce the I/O bottleneck have been also exprored. Thread-parallelization of the sparse linear solve is explored also through use of the SuperLU_MT library. Based on performance profiling results for the implicit method, the majority of CPU time is spent on the integration steps. Hence, in order to further improve the ETMSP performance, a variable time step control scheme for the original trapezoidal integration method has been developed and implemented. The Adams-Bashforth-Moulton predictor-corrector method was introduced and designed for ETMSP. Test results show superior performance with this method.
 

This paper presents an overview of the research project “High-Performance Hybrid Simulation/Measurement-Based Tools for Proactive Operator Decision-Support”, performed under the auspices of the U.S. Department of Energy grant DE-OE0000628. The objective of this project is to develop software tools to provide enhanced real-time situational awareness to support the decision making and system control actions of transmission operators. The integrated tool will combine high-performance dynamic simulation with synchrophasor measurement data to assess in real time system dynamic performance and operation security risk. The project includes: (i) The development of high-performance dynamic simulation software; (ii) the development of new computationally effective measurement-based tools to estimate operating margins of a power system in real time using measurement data from synchrophasors and SCADA; (iii) the development a hybrid framework integrating measurement-based and simulation-based approaches, and (iv) the use of cutting-edge visualization technology to display various system quantities and to visually process the results of the hybrid measurement-base/simulation-based security-assessment tool. Parallelization and high performance computing are utilized to enable ultrafast transient stability analysis that can be used in a real-time environment to quickly perform “what-if” simulations involving system dynamics phenomena. EPRI's Extended Transient Midterm Simulation Program (ETMSP) is modified and enhanced for this work. The contingency analysis is scaled for large-scale contingency analysis using MPI-based parallelization. Simulations of thousands of contingencies on a high performance computing machine are performed, and results show that parallelization over contingencies with MPI provides good scalability and computational gains. Different ways to reduce the I/O bottleneck have been also exprored. Thread-parallelization of the sparse linear solve is explored also through use of the SuperLU_MT library. Based on performance profiling results for the implicit method, the majority of CPU time is spent on the integration steps. Hence, in order to further improve the ETMSP performance, a variable time step control scheme for the original trapezoidal integration method has been developed and implemented. The Adams-Bashforth-Moulton predictor-corrector method was introduced and designed for ETMSP. Test results show superior performance with this method.