[[Latest] High quality journals of China Association for Science and Technology IEEE Journals Summary 2024 Update] Since 2019, China Association for Science and Technology has guided and supported its national societies to issue a classified catalog of high-quality journals for domestic and foreign scientific and technological journals in various disciplines based on the principle of "peer review, value orientation, and homogeneity and equivalence", It provides reference for scientific and technological workers to publish papers and scientific research institutions to carry out academic evaluation. By the end of November 2023, 43 national societies had completed the preparation of the first edition of the classification catalogue in their fields, and 6 societies had optimized and adjusted the published catalogue for the reference of relevant institutions. According to this summary version, this paper integrates IEEE related journals. IEEE (Institute of Electrical and Electronics Engineers), as the world's largest non-profit professional technology society, has technical authority in the fields of electrical and electronics, computers, semiconductors, communications, power energy, biomedical engineering, aerospace systems engineering, consumer electronics, etc. In a wide range of scientific and technological fields, IEEE journals are summarized in the hierarchical directory of high-quality scientific and technological journals. See the original text for specific fields: https://mp.weixin.qq.com/s/8PWcCchf3NbHOtKS-Z3JaQ 。

[What is general artificial intelligence?] For the public, AI (artificial intelligence) can be said to be very common and familiar. But what about AGI (Artificial General Intelligence)? It is a concept that has been discussed in science fiction and philosophy for a long time. It refers to AI with reasoning ability similar to human beings. When chat robots and generative artificial intelligence gradually come into the sight of the consumer public, AI has mastered a certain self-learning ability, and the speed of technology iteration has been greatly improved. However, most experts realize that they cannot reason as humans do. Karthik K., a member of IEEE, believes that although many breakthroughs have been made, generative AI lacks the reasoning ability similar to human beings, because it operates based on patterns and data without mastering their meaning, and cannot extend the concepts learned to new use scenarios. https://mp.weixin.qq.com/s/ztGQLciNntBTFTkugxEtoQ 。

Scan the WeChat QR code below to follow the "IEEE Institute of Electrical and Electronics Engineers" public account

[315 Expose the problem of data privacy. How can enterprises take the compulsory course of data privacy protection?] Many people have the experience that after browsing some websites on their mobile phones, they immediately receive sales calls from relevant industries. Many people wonder why the marketing staff of these companies who make harassing calls can accurately obtain their browsing behavior and contact information without leaving personal information such as phone calls? This is the abuse of data privacy exposed at the 315 party this year: some technology companies use big data technology to obtain users' personal information and online behavior, and provide it to marketing companies, forming a black industry chain of using big data to make harassing calls. Once the news was reported, public opinion broke out in an instant. Coincidentally, in recent years, data abuse and adverse data privacy protection have occurred frequently, involving many fields such as science and technology, finance, education, etc., which has also made data security related topics the focus for many times, which has driven the industry to think about how to take the required course of data privacy protection:

That is, in today's booming digital economy, data has become the most important factor of production for enterprises. In the face of gradually improved data laws and regulations, and increasingly rampant data black production, how should enterprises build their data security compliance system to protect their business; How should enterprises use data safely and legally to maximize the value of data?

At present, IEEE and IAPP training on data privacy and security is increasingly popular because these courses absorb the practical experience of global data security and privacy protection, can help enterprises understand the advantages and challenges of emerging technologies, help enterprises build data security and control mechanisms, and provide practical technical knowledge and cases System construction and other aspects help enterprises improve data security strategies.

IEEE is one of the largest professional and technical organizations in the world, which has published 30% of the world's electronic and electrical and computer science literature. In addition, it has formulated more than 1200 current industrial standards and 25 draft IEEE standards related to data privacy; As the largest and comprehensive global information privacy association in the world, IAPP has been committed to defining, supporting and improving the privacy protection industry worldwide for many years, and helping various companies and institutions manage and protect data. Taking the IEEE | IAPP data privacy engineering database series courses jointly launched by IEEE and IAPP as an example, this series of courses focuses on building trust and transparency in the product development cycle, provides comprehensive training courses and resource content for data privacy professionals, and helps relevant people understand how to manage network security risks and use data prudently.

More courses can be found in the original: https://mp.weixin.qq.com/s/nBsrvqifbNxMVQwAs4iw8A