How Generative Adversarial Networks Promote the Development of Intelligent Transportation Systems:A Survey

In current years,the improvement of deep learning has brought about tremendous changes:As a type of unsupervised deep learning algorithm,generative adversarial networks(GANs)have been widely employed in various fields including transportation.This paper reviews the development of GANs and their applications in the transportation domain.Specifically,many adopted GAN variants for autonomous driving are classified and demonstrated according to data generation,video trajectory prediction,and security of detection.To introduce GANs to traffic research,this review summarizes the related techniques for spatio-temporal,sparse data completion,and time-series data evaluation.GAN-based traffic anomaly inspections such as infrastructure detection and status monitoring are also assessed.Moreover,to promote further development of GANs in intelligent transportation systems(ITSs),challenges and noteworthy research directions on this topic are provided.In general,this survey summarizes 130 GAN-related references and provides comprehensive knowledge for scholars who desire to adopt GANs in their scientific works,especially transportation-related tasks.

Treatment of herniated lumbar disc by percutaneous laser disc decompression combined with synchronous suction technique through syringe

Objective： To compare the outcomes of percutaneous laser disc decompression （PLDD） and PLDD with synchronous suction through syringe in the patients with herniated lumbar disc（HLD）. Methods： Forty-two patients with HLD on MRI and those who did not respond to conservative treatment for 6 weeks were randomly divided into group A and group B. In group A, the patients were treated with PLDD and those in group B with PLDD and synchronous suction through syringe. GaAIAS diode laser at 810 nm was used for the ablation in both groups. The treatment effect was evaluated by modified MacNab＇s criteria on the 7^th, 30^th and 90^th day. Results： Evaluated by modified MacNab＇s criteria, the percentages of the excellent and good cases in total patients treated for group B and A were 80.95% and 57.14% on the 7^th follow-up day, 85.71% and 66.67% on the 30^th follow-up day, and 95.24% and 71.43% on the 90^th follow-up day, respectively. Conclusion： Synchronous suction technique through syringe during PLDD improves the overall outcome in the treatment of herniated lumbar disc.

Evaluation on China＇s Anti-drug Efforts and Recommendations

China, the East Asian giant, now faces a growing problem of illicit drug use, which is deeply harmful to its stability. The outcome of intensive enforcements, named ＂People＇s anti-drug war＂, though reaching some accomplishments, is still insufficient to settle this increasingly serious problem. This essay, therefore, highlights the four limits of China＇s current lawful enforcement through examining the outcome of ＂anti-drug war＂ launched in 2015. Furthermore, the essay provides four potential recommendations for the adjustment in China＇s anti-drug strategy, in terms of its particular political system and geographical environment. With the increasing younger-age trend and geographical expansion of illicit drug problem, the serious situation is calling for a more flexible and artful regulatory framework in China.

Envisioning the future of transportation:Inspiration of ChatGPT and large models

1.Introduction Traditional artificial intelligence(AI)strategies,reliant on manually crafted patterns or task-specific feature representations,often suffer from overfitting and struggle with the dynamic nature of real-world scenarios.In contrast,the current AI landscape is witnessing a significant departure from conventional methods,exemplified by the rise of generative and large models like Chat Generative Pre-Trained Transformer(ChatGPT).They not only offer broad functionalities for diverse applications but are also designed for intuitive interpretation,application,and adaptability to emerging tasks and domains.

Future role of artificial intelligence in advancing transportation electrification

1 Introduction Over the past decade,the rapid evolution of artificial intelligence(AI)has revolutionized various sectors,including transportation.This discussion explores the transformative potential of AI in enhancing transportation electrification,focusing on its role in battery management,vehicle speed regulation,and personalized route recommendations for Autonomous Electric Vehicles(AEVs).