Search

As a rapidly developing airline company in the international market, Air China has lived up to expectations and worked hard to develop its uniqueness in terms of policies and regulations, economic conditions, operating environment, social factors, and scientific and technological levels. Since 2021, Air China has been promoting pollution reduction and low-carbon development, leading green aviation and building a better home", and fighting the battle against pollution has become the key task of the company's 14th Five-Year Plan. This paper reviews the background, vision, and innovative greenhouse gas (GHG) reduction strategic plan for the Air China Limited. The innovative aspect and impact analysis of the GHG business in terms of services and/or products have been critically reviewed within the paper via SWOT method.

This report explains Coordinating the overall situation at China and abroad during 20 years. Considering the importance of domestic and foreign situations, China needs to adopt a global perspective, strengthen strategic thinking, grasp development opportunities, and respond to risks and challenges in the context of changes in the international situation. The report also put forward the requirements of enterprise innovation, through the courage to change, the courage to innovate and never fossilized, never stagnant efforts, not to be afraid of any risks, not to be confused by any interference of the firm will, promote the theoretical innovation, institutional innovation, cultural innovation.

This article takes editions as the main object of study, based on the "Edition Review of Modern Chinese Long Novel Masterpieces" and analyzes "Ni Huanzhi". In this book, the author proposes that the most suitable object of edition criticism is the long novel, because the edition content of the novel is the most complex and rich. Its long length cannot be compared with that of drama editions; its edition density is so high that it cannot be compared with that of poetry and prose editions.

During the current post-epidemic period, hygiene requirements and health needs in the hospitality industry keep increasing, and consumers become more concerned about the cleanliness of hotels and have stronger demands for contactless services in hotels. The growth and popularity of IoT technology in China make it more accessible to a wider range of service industries and provides the basis for the application of IoT in the hospitality industry. The application of IoT devices in hotels mainly includes intelligent robots, intelligent guest control, systems, etc., which helps to realize contactless services in hotels. This research reviews the entire development cycle of the application of IoT in the hospitality industry, from the founding, development, and expansion of companies to their IPO and post-IPO maturity. From a perspective combined with IoT technology, we can cope with the changing industry models, business models, and operation modes in the hospitality industry more efficiently. The development of IoT in hotels will move towards humanization and service-orientation. Through the role of human–machine linkage and the reasonable management of IoT equipment, IoT technology can reasonably promote the efficiency of manual work, while injecting “warmth” and “quality” into IoT equipment.

Convolutional neural networks (CNN) have made remarkable achievements in speech enhancement. However, the convolution operation is difficult to obtain the global context of the feature map due to its locality. To solve the above problem, we propose an attention-augmented fully convolutional neural network for monaural speech enhancement. More specifically, the method is to integrate a new two-dimensional relative selfattention mechanism into fully convolutional networks. Besides, we utilize Huber Loss as the loss function, which is more robust to noise. Experimental results indicate that compared with the optimally modified log-spectral amplitude (OMLSA) estimator and other CNN-based models, our proposed network has better performance in five indicators, and can well balance noise suppression and speech distortion. What is more, we also embed the proposed attention mechanism into other convolutional networks and get satisfactory results, showing that this mechanism has great generalization ability.