Artificial Intelligence, Technological Innovation and the Upgrading of China’s Equipment Manufacturing Industry

This article identifies and screens out companies applying Artificial Intelligence (AI) through Enterprise Search, and measures the level of AI empowerment in the industry in terms of the number of companies applying AI as a proportion of the number of companies in the industry as a whole, and based on the panel data of China’s equipment manufacturing industry from 2001-2017, we empirically test the impact effect and mechanism of action of AI empowerment on the upgrading of the equipment manufacturing industry. The research results show that: AI empowerment has a significant positive impact on the upgrading of the equipment manufacturing industry, but there is industry heterogeneity, and AI empowerment has a greater positive impact effect on the upgrading of the high-end equipment manufacturing industry. Technological innovation plays a mediating role in the process of AI empowerment for the upgrading of equipment manufacturing

Integrated Sensing, Computation, and Communication: System Framework and Performance Optimization

Integrated sensing, computation, and communication (ISCC) has been recently considered as a promising technique for beyond 5G systems. In ISCC systems, the competition for communication and computation resources between sensing tasks for ambient intelligence and computation tasks from mobile devices becomes an increasingly challenging issue. To address it, we first propose an efficient sensing framework with a novel action detection module. It can reduce the overhead of computation resource by detecting whether the sensing target is static. Subsequently, we analyze the sensing performance of the proposed framework and theoretically prove its effectiveness with the help of the sampling theorem. Then, we formulate a sensing accuracy maximization problem while guaranteeing the quality-of-service (QoS) requirements of tasks. To solve it, we propose an optimal resource allocation strategy, in which the minimal resource is allocated to computation tasks, and the rest is devoted to sensing tasks. Besides, a threshold selection policy is derived. Compared with the conventional schemes, the results further demonstrate the necessity of the proposed sensing framework. Finally, a real-world test of action recognition tasks based on USRP B210 is conducted to verify the sensing performance analysis, and extensive experiments demonstrate the performance improvement of our proposal by comparing it with some benchmark schemes

Environment-Centric Safety Requirements forAutonomous Unmanned Systems

Autonomous unmanned systems (AUS) emerge to take place of human operators in harsh or dangerous environments. However, such environments are typically dynamic and uncertain, causing unanticipated accidents when autonomous behaviours are no longer safe. Even though safe autonomy has been considered in the literature, little has been done to address the environmental safety requirements of AUS systematically. In this work, we propose a taxonomy of environment-centric safety requirements for AUS, and analyse the neglected issues to suggest several new research directions towards the vision of environment-centric safe autonomy

A review of interactive narrative systems and technologies: a training perspective

As an emerging form of digital entertainment, interactive narrative has attracted great attention of researchers over the past decade. Recently, there is an emerging trend to apply interactive narrative for training and simulation. An interactive narrative system allows players to proactively interact with simulated entities in a virtual world and have the ability to alter the progression of a storyline. In simulation-based training, the use of an interactive narrative system enables the possibility to offer engaging, diverse and personalized narratives or scenarios for different training purposes. This paper provides a review of interactive narrative systems and technologies from a training perspective. Specifically, we first propose a set of key requirements in developing interactive narrative systems for simulation-based training. Then we review nine representative existing systems with respect to their system architectures, features and related mechanisms. To examine their applicability to training, we investigate and compare the reviewed systems based on the functionalities and modules that support the proposed requirements. Furthermore, we discuss some open research issues on future development of interactive narrative technologies for training applications

Video Surveillance Over Wireless Sensor and Actuator Networks Using Active Cameras

Although there has been much work focused on the camera control issue on keeping tracking a target of interest, few has been done on jointly considering the video coding, video transmission, and camera control for effective and efficient video surveillance over wireless sensor and actuator networks (WSAN). In this work, we propose a framework for real-time video surveillance with pan-tilt cameras where the video coding and transmission as well as the automated camera control are jointly optimized by taking into account the surveillance video quality requirement and the resource constraint of WSANs. The main contributions of this work are: i) an automated camera control method is developed for moving target tracking based on the received surveillance video clip in consideration of the impact of video transmission delay on camera control decision making; ii) a content-aware video coding and transmission scheme is investigated to save network node resource and maximize the received video quality under the delay constraint of moving target monitoring. Both theoretical and experimental results demonstrate the superior performance of the proposed optimization framework over existing systems

Study on the Applicable Conditions for Protective Left-Turn Phase and Permissive Left-Turn Phase

In order to improve the operation efficiency of intersections and make traffic management more scientific, this paper conducts a research on the application conditions for protective left-turn phase and permissive left-turn phase. Taking the traffic efficiency model as a constraint and VISSIM simulation as research means, this paper makes a comparative analysis of the traffic efficiency under different flow conditions using different control means, so as to obtain the specific traffic flow conditions applicable to different control means. This research aims to provide data support for the scientific application of traffic management

Phylogenetic analysis of birne shrimp (Aretemia) in China using DNA barcoding

DNA barcoding is a powerful approach for characterizing species of organisms, especially those with almost identical morphological features, thereby helping to to establish phylogenetic relationships and reveal evolutionary histories. In this study, we chose a 648-bp segment of the mitochondrial gene, cytochrome c oxidase subunit 1 (COI), as a standard barcode region to establish phylogenetic relationships among brine shrimp (Artemia) species from major habitats around the world and further focused on the biodiversity of Artemia species in China, especially in the Tibetan Plateau. Samples from five major salt lakes of the Tibetan Plateau located at altitudes over 4,000m showed clear differences from other Artemia populations in China. We also observed two consistent amino acid changes, 153A/V and 183L/F, in the COI gene between the high and low altitude species in China. Moreover, indels in the COI sequence were identified in cyst and adult samples unique to the Co Qen population from the Tibetan Plateau, demonstrating the need for additional investigations of the mitochondrial genome among Tibetan Artemia populations

A Remote Markerless Human Gait Tracking for E-Healthcare Based on Content-Aware Wireless Multimedia Communications

Remote human motion tracking and gait analysis over wireless networks can be used for various e-healthcare systems for fast medical prognosis and diagnosis. However, most existing gait tracking systems rely on expensive equipment and take lengthy processes to collect gait data in a dedicated biomechanical environment, limiting their accessibility to small clinics located in remote areas. In this work we propose a new accurate and cost-effective e­ healthcare system for fast human gait tracking over wireless networks, where gait data can be collected by using advanced video content analysis techniques with low-cost cameras in a general clinic environment. Furthermore, based on video content analysis, the extracted human motion region is coded, transmitted, and protected in video encoding with a higher priority against the insignificant background area to cope with limited communication bandwidth. In this way the encoder behavior and the modulation and coding scheme are jointly optimized in a holistic way to achieve the best user-perceived video quality over wireless networks. Experimental results using H.264/AVC demonstrate the validity and efficacy of the proposed system

Prefix-diffusion: A Lightweight Diffusion Model for Diverse Image Captioning

While impressive performance has been achieved in image captioning, the limited diversity of the generated captions and the large parameter scale remain major barriers to the real-word application of these systems. In this work, we propose a lightweight image captioning network in combination with continuous diffusion, called Prefix-diffusion. To achieve diversity, we design an efficient method that injects prefix image embeddings into the denoising process of the diffusion model. In order to reduce trainable parameters, we employ a pre-trained model to extract image features and further design an extra mapping network. Prefix-diffusion is able to generate diverse captions with relatively less parameters, while maintaining the fluency and relevance of the captions benefiting from the generative capabilities of the diffusion model. Our work paves the way for scaling up diffusion models for image captioning, and achieves promising performance compared with recent approaches.Comment: 11 pages,4 figures, 6 table