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.

The highly dynamic nature of the cyber domain demands that cyber operators are capable of rapidly evolving and adapting with exquisite timing. These forces, in turn, pressure acquisition specialists to accoutre cyber warfighters to keep pace with both cyber domain advancement and adversary progression. However, in the Department of Defense (DoD), a vigorous tug of war exists between time and risk pressures. Risk reduction is a crucial element of managing any complex enterprise and this is particularly true for the DoD and its acquisition program [1]. This risk aversion comes at significant cost, as obsolescence by risk minimization is a real phenomenon in DoD acquisition programs and significantly limits the adaptability of its operational cyber forces. Our previous research generated three recommendations for reforming policy to deliver performance at the “speed of relevance” [3]. In this paper we focus on one of the recommendations: “Manage rather than avoid risk—especially time-based risks”. While this advice can apply to many areas of human endeavor, it has elevated urgency in cyberspace. Incomplete risk metrics lead to overly conservative acquisition efforts that imperil timely procurement of advanced cyber capabilities and repel innovators. Effective cyber defense operations require acquisition risk models to be extended beyond fiscal and technical risk metrics of performance, to include risks associated with the cost of failing to meet immediate mission requirements. This paper proposes a time-shifting approach to simultaneously (a) accelerate capability delivery while maintaining traditional rigor, and (b) achieve optimal balance between fiscal, performance, and time risks.

Diagnostic research methods were designed to draw attention to the needs of future engineers in the field of innovative methods of acquiring knowledge, skills and competencies in the protection of intellectual property in order to prepare for functioning in the economy 4.0.