Abstract-In order to confirm the theoretical knowledge it is important to perform experiments while learning the digital circuit design, which enhances the learning process. The digital design laboratories are often in short supply and introduces a number of limitations. The limitations includes smaller number of instruments and instrument stability, particularly in poor and developing countries. This paper reports the development of a mobile virtual laboratory application (VL-APP) digital design that help students to perform virtual experiments anywhere and anytime. It mainly utilizes simulation of experiments and provides a model and script for users to design experiments independently. The development utilizes Unity3D and 3ds-max for the software platform, and Android for the test installation environment. The test results demonstrates potential of the developed application.

Abstract. The paper presents a Chinese philosophical point of view of AI, and presents a novel system of the AI machine. There are two basic relations or contradictions which drive computer developments forward. One is between software and hardware and the other is between data structure and system organization. It is suggested that a description of a future AI system should primarily start from these contradictions.

E-commerce logistics course is the professional and core courses of E-commerce major. In real teaching, due to many reasons, many problems emerged, such as students' enthusiasm for learning is not high, the learning effect is not good, and students are not equipped with practical ability. In this situation, Based on the production-education integration, combined with the capacity demand of enterprise logistics position, depending on project training, skill competition and enterprise practice, this paper puts forward some reasonable proposals on the teaching content and teaching method in order to cultivate the e-commerce logistics compound talents.

Due to the rapid development of information, the image recognition method based on the artificial intelligence algorithm has been applied to many application fields. As the product of modern information technology, the image recognition method based on the artificial intelligence algorithm is also a significant and pioneering research topic. With the development of digital image processing technology and the updating of computer electronic products, digital image processing technology has been applied to various fields and has made great contributions to the progress of science and technology and the development of productivity. Image processing methods cover a wide range of application fields, including image conversion, restoration, separation, enhancement and matching, and classification. In order to explore the application of the AI algorithm in image processing, on the basis of the latest BAS algorithm discovered recently, we have established a brand-new hybrid intelligent algorithm BAS based on C as computing, which is applied to multiple image processing fields and achieves good optimization results. Studying the problems and future development directions in the application is conducive to promoting such development of image recognition technology and is conducive to applying image recognition technology to more fields.

This paper aims to provide insight into the driving distraction domain systematically on the basis of scientific knowledge graphs. For this purpose, 3,790 documents were taken into consideration after retrieving from Web of Science Core Collection and screening, and two types of knowledge graphs were constructed to demonstrate bibliometric information and domain-specific research content respectively. In terms of bibliometric analysis, the evolution of publication and citation numbers reveals the accelerated development of this domain, and trends of multidisciplinary and global participation could be identified according to knowledge graphs from Vosviewer. In terms of research content analysis, a new framework consisting of five dimensions was clarified, including “objective factors”, “human factors”, “research methods”, “data” and “data science”. The main entities of this domain were identified and relations between entities were extracted using Natural Language Processing methods with Python 3.9. In addition to the knowledge graph composed of all the keywords and relationships, entities and relations under each dimension were visualized, and relations between relevant dimensions were demonstrated in the form of heat maps. Furthermore, the trend and significance of driving distraction research were discussed, and special attention was given to future directions of this domain.