Does The Implementation Of ERP Improve The Quality Of Accounting Information? Evidence From Chinese A-Share Listed Manufacturing Firms

Using the data of Chinese A-share listed manufacturing firms, the study explores the influence of ERP implementation on accounting information quality from reliability and relevance. Also, the study verifies the difference of the influence in firms which have different sizes and different ownership types. Compared with the firms not implementing ERP, accounting information quality of the firms implementing ERP improves significantly. In addition, the positive influence differs in firms of different sizes and different ownership types. In large-sized firms, ERP implementation has stronger influence on reliability of accounting information. In non-state-owned firms, ERP implementation has stronger influence on accounting information quality in respect to reliability and relevance. Our study supplies the new evidence to gauge the impact of ERP implementation on accounting information quality in an emerging economy context

Investigation on Start-up and Reliability during Unsteady Process of Low Temperature Air Source Heat Pump

In this paper the air source heat pump variable refrigerant flow (VRF) of two-stage vapor injection system were analyzed, to investigate the compressor start-up performance at low ambient temperature and the system reliability during unsteady operating process. The start-up control logic of VRF were designed, which combined the control of the electronic expansion valves (EEV), the oil switch valve (SV) and the elevator rate of compressor frequency, to achieve the unit steadily started up at -35℃. In the study on the reliability during unsteady process of the system, the phenomena of the refluence vapor and the enthalpy increasing by vapor injection flowing with liquid, and the trend of the system parameter at their critical state were researched. Besides, the relation of the compression ratio at low stage and the volume ratio of high stage to low stage was gained at refluence state, and it was validated with the experiment in the unit. The experimental results of the VRF showed that the critical compression ratio of low stage at refluence state was close to the reciprocal of the volume ratio, and the refluence didn’t happen when the volume ratio was 1.0

Scaling Pre-trained Language Models to Deeper via Parameter-efficient Architecture

In this paper, we propose a highly parameter-efficient approach to scaling pre-trained language models (PLMs) to a deeper model depth. Unlike prior work that shares all parameters or uses extra blocks, we design a more capable parameter-sharing architecture based on matrix product operator (MPO). MPO decomposition can reorganize and factorize the information of a parameter matrix into two parts: the major part that contains the major information (central tensor) and the supplementary part that only has a small proportion of parameters (auxiliary tensors). Based on such a decomposition, our architecture shares the central tensor across all layers for reducing the model size and meanwhile keeps layer-specific auxiliary tensors (also using adapters) for enhancing the adaptation flexibility. To improve the model training, we further propose a stable initialization algorithm tailored for the MPO-based architecture. Extensive experiments have demonstrated the effectiveness of our proposed model in reducing the model size and achieving highly competitive performance.Comment: 14 pages, 4 figures, 6 table

Implications for functional diversity conservation of China’s marine fisheries

Publisher Copyright: Copyright © 2022 Zhao, He, Su, Xu, Xu, Zhang and Zhang.Functional diversity is critical to ecosystem stability and resilience to disturbances as it supports the delivery of ecosystem services on which human societies rely. However, changes in functional diversity over space and time, as well as the importance of particular marine fish species to functional space are less known. Here, we reported a temporal change in the functional diversity of marine capture fisheries from all coastal provinces in China from 1989 to 2018. We suggested that both functional evenness (FEve) and functional divergence (FDiv) changed substantially over time, especially with considerable geographic variation in FEve in the detected patterns. Even within the same sea, the relative contributions of fishes with various water column positions and trophic levels in different waters have different patterns. Together these results underline the need of implementing specific climate-adaptive functional diversity conservation measures and sustainable fisheries management in different waters.Peer reviewe

Research on Chinese Intelligent Guanglianda in High-rise Construction

Since the reform and opening up in China, the rapid development of China's construction industry, especially after 2011, BIM technology in China has a rapid development and depth of application. This article mainly discusses the process of development of China's construction industry management and the process of development of BIM technology in China and, the use of software in China, the main use of revit in 3D modeling (design stage), the use of Guanglianda in the whole process of construction management. This article researches on Guanglianda and the applications were described, for example, in the integrated project of management information, labor management information, construction video surveillance, material management, material site acceptance. This paper also elaborates on the cooperation of Revit and Guanglianda in different stages. This paper also elaborates on a construction case in China, and makes a description of the problems of crane, facts and time, and then explores the reasons behind the rapid construction of China. And the feasibility of China's construction management approach to the introduction of Russia

TikTalk: A Video-Based Dialogue Dataset for Multi-Modal Chitchat in Real World

To facilitate the research on intelligent and human-like chatbots with multi-modal context, we introduce a new video-based multi-modal dialogue dataset, called TikTalk. We collect 38K videos from a popular video-sharing platform, along with 367K conversations posted by users beneath them. Users engage in spontaneous conversations based on their multi-modal experiences from watching videos, which helps recreate real-world chitchat context. Compared to previous multi-modal dialogue datasets, the richer context types in TikTalk lead to more diverse conversations, but also increase the difficulty in capturing human interests from intricate multi-modal information to generate personalized responses. Moreover, external knowledge is more frequently evoked in our dataset. These facts reveal new challenges for multi-modal dialogue models. We quantitatively demonstrate the characteristics of TikTalk, propose a video-based multi-modal chitchat task, and evaluate several dialogue baselines. Experimental results indicate that the models incorporating large language models (LLM) can generate more diverse responses, while the model utilizing knowledge graphs to introduce external knowledge performs the best overall. Furthermore, no existing model can solve all the above challenges well. There is still a large room for future improvements, even for LLM with visual extensions. Our dataset is available at \url{https://ruc-aimind.github.io/projects/TikTalk/}.Comment: Accepted to ACM Multimedia 202

Efficient robust control of mixed platoon for improving fuel economy and ride comfort

The emergence of connected and automated vehicle technology has improved the operational efficiency of mixed traffic systems. This paper studies a two-tier trajectory optimization problem for mixed platooning to improve fuel efficiency, ride comfort, and operational safety during vehicle operations. The proposed model follows a two-tier control logic to plan the trajectory of platooning vehicles with three objectives, including minimizing fuel consumption, maximizing ride comfort, and enhancing the anti-disturbance performance of the platoon. The first is the planning tier, which aims to design the optimal trajectory for Connected and Automated Vehicles (CAVs) based on the optimal fuel consumption and comfort and obtain the expected acceleration curve of CAV. The second is the control tier, which aims to ensure the safe operation of platooning vehicles in the presence of uncertain disturbances in real time. Specifically, we propose a robust tube MPC control method, which dynamically adjusts the CAV acceleration according to the reference trajectory obtained by the planning tier to resist the effects of uncertain disturbances, and the tracking behaviour of Human-Driven Vehicles (HDVs) is offline solved by the robust optimal velocity model. Finally, we design simulation experiments to verify the effectiveness of the proposed two-tier optimization framework. The experimental results show the effectiveness and advantages of the two-tier framework in terms of fuel economy, ride comfort, and robustness against different noise disturbances

Joint optimization of platoon control and resource scheduling in cooperative vehicle-infrastructure system

Vehicle platooning technology is essential in achieving group consensus, on-road safety, and fuel-saving. Meanwhile, Vehicle-to-Infrastructure (V2I) communication significantly facilitates the development of connected vehicles. However, the coupled effects of the longitudinal vehicle’s mobility, platoon control and V2I communication may result in a low reliable communication network between the platoon vehicle and the roadside unit, there is a tradeoff between the platoon control and communication reliability. In this paper, we investigate a biobjective joint optimization problem where the first objective is to maximize the success probability of data transmission (communication reliability) and the second objective function is to minimize the traffic oscillation flow. The vehicle’s mobility state of the platoon vehicle affects the channel capacity and transmission performance. In this context, we deeply explore the relationship between control signals and resource scheduling and theoretically deduce a closed-form expression of the optimal communication reliability objective. Through this closed expression, we transform the bi-objective model into a single objective MPC model by using ϵ-constraint method. We design an efficient algorithm for solving the joint optimization model and prove the convergence. To verify the effectiveness of the proposed method, we finally evaluate the spacing error, speed error, and resource scheduling of platooning vehicles through simulation experiments in two experimental scenarios. The results show that the proposed control-communication co-design can improve the platoon control performance while satisfying the high reliability of V2I communications