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A Study and Improvement of Project Progress Evaluation Methods Based on the Microservice-Driven Post-Evaluation Framework for technology Projects 4

A Study and Improvement of Project Progress Evaluation Metho...

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4th International Conference on Big Data Economy and information Management, BDEIM 2023

作者： Gao, Xiaoxin Liu, Yongqing Sun, Ming He, Jiyuan Jia, Meng Zhang, Ying Beijing China-Power Information Technology Co. Ltd. China State Grid Information & Telecommunication Group Co. Ltd. China School of Control and Computer Engineering North China Electric Power University China

ISBN: (纸本)9798400716669

In electric power industry, the lack of post-evaluation system for science and technology projects leads to problems such as incomplete evaluation, lack of scientific basis, missing improvement opportunities and lowering decision-making level. Therefore, the establishment of the post-evaluation system of science and technology projects is very important to improve the level of science and technology and promote the development of the industry. This paper proposes a post-evaluation system for science and technology projects based on micro-service architecture, which adopts the separation mode of front and back end to evaluate and analyze the science and technology projects of State Grid. Through modular micro-service architecture and unified interface standard, the system realizes five modules: science and technology project data management, index system establishment, project classification, index evaluation and expert evaluation. The system can comprehensively evaluate the effectiveness and quality of scientific and technological projects, present the results in an easy-to-understand manner, provide scientific basis, and improve the level of decision-making. At the same time, we will systematically promote scientific project structure, improve fund utilization, measure project quality and promote low-carbon development. This study provides important guidance and support for the technological development of electric power enterprises. © 2023 ACM.

关键词： Microservice architecture Post-evaluation for science and technology projects Power grid

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Offloading Model of 5G Intelligent Terminal Based on UC-MEC and Node Consensus Mechanism 15

Offloading Model of 5G Intelligent Terminal Based on UC-MEC ...

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15th IEEE International Conference on Wireless communications and Signal Processing, WCSP 2023

作者： Wang, Lei Su, Yufei Dou, Haie Cui, Jingwu Zheng, Baoyu Nanjing University of Posts and Telecommunications School of Communications and Information Engineering Nanjing China Nanjing University of Posts and Telecommunications Ministry of Education Key Lab of Broadband Wireless Communication and Sensor Network Technology Nanjing China

ISBN: (纸本)9798350324662

Offloading for 5G intelligent terminals is an important requirement of mobile edge computing (MEC), which can reduce the load of terminal devices and provide more powerful computing power and services. However, due to the interference between different users and the waste of a lot of resources, the role of MEC is greatly limited. In the article, energy-saving blockchain technology is introduced into the user-centric MEC (UC-MEC) system. However, in UC-MEC, it is necessary to comprehensively consider task offloading and energy consumption optimization in the consensus process to improve overall energy efficiency. To solve these problems, a new offloading model of 5G intelligent terminal is proposed, which realizes safe and efficient resource utilization by jointly optimizing the bandwidth and computing resource allocation of access point (AP). The research also proposed a resource consensus mechanism based on Zookeeper atomic broadcast (RC-ZAB), and the parallel optimization framework of relaxed hybrid alternative direction method of multipliers (RH-ADMM) to solve the problems of resource transaction and energy consumption optimization. The experimental results show that compared with the comparison method, the total energy consumption of the proposed method is reduced by 41.39% at most, and the total delay is reduced by 29.80% at most. © 2023 IEEE.

关键词： blockchain Mobile edge computing resource consensus task offloading user-centric

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A Morphing Quadrotor with Transformable Arms: Modelling, control and Simulation

A Morphing Quadrotor with Transformable Arms: Modelling, Con...

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Youth Academic Annual Conference of Chinese Association of Automation (YAC)

作者： Yubo Liu Shengming Li School of Information and Communication Engineering School of Innovation and Entrepreneurship of DUT Dalian University of Technology Dalian P. R. China

ISBN: (数字)9798350379228

ISBN: (纸本)9798350390780

A novel morphing quadrotor (MQ) that can adapt to variable task and environment is proposed in this paper. The MQ includes two deformable multi-link support arms that can alter its shape to cross narrow spaces, which increases the versatility of quadrotors. A dynamic model of the MQ is constructed by the Newton-Euler approach, which involves the dynamic of two morphing support arms that will not appear in the conventional multi-rotor UAVs with fixed geometry. Based on the dynamic model, a nonlinear controller is designed to address the attitude stability control of MQ during deformation. Ultimately, the stability of the proposed attitude controller is proved through the Lyapunov method, and numerical simulation tests are performed to validate the effectiveness of the developed MQ system.

关键词： Analytical models Attitude control Shape Numerical simulation Stability analysis Numerical models Nonlinear dynamical systems

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Research on Filter Bank Multi Carrier Deep Receiver in 5G System 2

Research on Filter Bank Multi Carrier Deep Receiver in 5G Sy...

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2nd International Seminar on Artificial Intelligence, Networking and information technology, AINIT 2021

作者： Li, Xuhong Gao, Yukai Wang, Anyi Xi'an University of Science and Technology School of Communication and Information Engineering Xi'an China

ISBN: (纸本)9781665412964

The multicarrier technology of the filter bank is one of the candidate waveforms for 5G, and its performance depends on the design of the prototype filter. However, the length of the prototype filter is much larger than the number of sub-channels, and the implementation complexity is high, which is not conducive to hardware implementation. In this paper, in order to improve the signal detection capability of the filter bank multi-carrier wireless communication (FBMC) system while reducing the implementation cost, we propose a Deep Receiver (receiver model) based on a neural network model to replace the signal detection and recovery at the traditional receiving end. The proposed Deep Receiver takes the received signal as input and the original information bit streams as output, which greatly simplifies the structure of the receiver. The experimental result shows that our algorithm has great detection and recovery ability and great robustness. © 2021 IEEE.

关键词： Filter banks

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Intelligent Passive Detection of Aerial Target in Space-Air-Ground Integrated Networks

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China communications 2022年第1期19卷 52-63页

作者： Mingqian Liu Chunheng Liu Ming Li Yunfei Chen Shifei Zheng Nan Zhao State Key Laboratory of Integrated Service Networks Xidian UniversityShaanxiXi’an 710071China Guilin Changhai Development Co. LtdGuilin 541001China School of Engineering University of WarwickCoventry CV47ALU.K. School of Information and Communication Engineering Dalian University of TechnologyDalian 116024China

Passive detection of moving target is an important part of intelligent surveillance. Satellite has the potential to play a key role in many applications of space-air-ground integrated networks(SAGIN). In this paper, we propose a novel intelligent passive detection method for aerial target based on reservoir computing networks. Specifically, delayed feedback networks are utilized to refine the direct signals from the satellite in the reference channels. In addition, the satellite direct wave interference in the monitoring channels adopts adaptive interference suppression using the minimum mean square error filter. Furthermore, we employ decoupling echo state networks to predict the clutter interference in the monitoring channels and construct the detection statistics accordingly. Finally, a multilayer perceptron is adopted to detect the echo signal after interference suppression. Extensive simulations is conducted to evaluate the performance of our proposed method. Results show that the detection probability is almost 100% when the signal-to-interference ratio of echo signal is-36 dB, which demonstrates that our proposed method achieves efficient passive detection for aerial targets in typical SAGIN scenarios.

关键词： aerial target detection decoupling echo state networks delayed feedback networks multilayer perceptron satellite illuminator space-air-ground integrated networks

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Integration of Artificial Intelligence and Wearable Internet of Things for Mental Health Detection

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International Journal of Cognitive Computing in engineering 2024年第1期5卷 307-315页

作者： Wang, Wei Chen, Jian Hu, Yuzhu Liu, Han Chen, Junxin Gadekallu, Thippa Reddy Garg, Lalit Guizani, Mohsen Hu, Xiping Guangdong-Hong Kong-Macao Joint Laboratory for Emotional Intelligence and Pervasive Computing Artificial Intelligence Research Institute Shenzhen MSU-BIT University Guangdong Shenzhen518172 China School of Medical Technology Beijing Institute of Technology Beijing100081 China School of Intelligent Systems Engineering Sun Yat-sen University Guangdong Shenzhen518000 China School of Software Dalian University of Technology Dalian116621 China Division of Research and Development Lovely Professional University Phagwara India Center of Research Impact and Outcome Chitkara University Punjab India Faculty of Information and Communication Technology University of Malta Msida Malta United Arab Emirates

The integration of Artificial Intelligence (AI) and Wearable Internet of Things (WIoT) for mental health detection is a promising area of research with the potential to revolutionize mental health monitoring and diagnosis. Since early detection of mental diseases, i.e., depression, is of great importance for diagnosis and treatment, a fast and convenient way is urgently needed. Traditional diagnostic methods are time-consuming, laborious, over-subjective, and easily lead to misdiagnosis. The advance in information techniques and wearable devices brings innovation to mental disease detection. Therefore, this article first compares intelligent depression detection methods and traditional methods to illustrate the significance and then analyzes the opportunities of the wearable device. Then we provide specific psychophysiological data measured by wearable devices and introduce relevant datasets for depression detection. An illustrative example of depression detection with sleep data is presented and discussed and our proposed ensemble method has improved nearly 10% to baselines. Analytical results demonstrate the great potential of using wearable device-measured psychophysiological data to detect depression intelligently. © 2024 The Authors

关键词： Internet of things

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Credible Remote Sensing Scene Classification Using Evidential Fusion on Aerial-Ground Dual-view Images

arXiv

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arXiv 2023年

作者： Zhao, Kun Gao, Qian Hao, Siyuan Sun, Jie Zhou, Lijian The School of Information and Control Engineering Qingdao University of Technology Qingdao266520 China

Multi-view (multi-source, multi-modal and multiperspective, etc.) data is increasingly used in remote sensing tasks because they can provide more useful information than single source data. However, data quality varies from view to view, limiting the potential benefits of multi-view data, which could be maximized by fusing them according to their credibility. Although recent deep learning based models are able to learn the weight of data adaptively, the lack of research on quantifying multi-view data credibility explicitly makes these models inexplicable, which affects their performance and flexibility in downstream remote sensing tasks. To fill this gap, in this paper, the theory of evidential deep learning is introduced to the aerial-ground dual-view remote sensing scene classification task to model the credibility of each view. Specifically, the theory of evidence is used to calculate an uncertainty value which describes the decision-making risk of each view. According to the uncertainty, a novel decision-level fusion strategy is proposed to make sure that the view with lower decision-making risk obtain more weight to make the classification more credible. Our approach achieved state-of-the-art performances on two classic public aerial-ground dual-view remote sensing image datasets, demonstrating the effectiveness of the proposed approach. Copyright © 2023, The Authors. All rights reserved.

关键词： Remote sensing

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Boosting Knowledge Graph with Diverse-Aware Intent Inference for Recommendations

SSRN

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SSRN 2024年

作者： Lv, Shaoqing Wang, Chichi Xiang, Ju Bao, Zhiqiang Li, Min School of Communication and Information Engineering Xi’an University of Posts and Telecommunications Xian China School of Computer and Communication Engineering Changsha University of Science and Technology Changsha China School of Computer Science and Engineering Central South University Changsha China

Knowledge graphs are highly effective for recommendation systems due to their rich semantic information. To address the limitations of traditional Collaborative Filtering and Embedding-based methods, methods based on Graph Neural networks (GNN) have been developed to model the complex relationships within knowledge graphs. However, existing GNN-based methods primarily focus on aggregating information from all neighborhoods of nodes, often leading to information redundancy. This redundancy results in two main issues: node representations can not reflect actual graph information and tend to select similar items thus detrimental to the system's diversity. To overcome these challenges, we propose Knowledge Graph with Diverse-Aware Intent Inference (KGDII). KGDII selects a diverse subset of relationships to generate intents for modeling user-item interactions. User intent represents the shared goals or motivations that drive users to make specific choices. We employ an attention mechanism to integrate relationships from the knowledge graph, assigning higher attention coefficients to more important relationships. This approach enables sampling a more diverse subset of relationships, thereby enriching the representation of user intents. Our proposed method demonstrates promising performance on real-world datasets, outperforming state-of-the-art methods. Additionally, ablation studies and case studies highlight the strong interpretability of KGDII compared to other methods. © 2024, The Authors. All rights reserved.

关键词： Recommender systems

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Ultra-high Resolution Full-Color OLEDs Patterned by Photo-Lithography

Ultra-high Resolution Full-Color OLEDs Patterned by Photo-Li...

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SID International Symposium Digest of Technical Papers, 2023

作者： Lee, Ryungyu Choi, Keun-Yeong Kweon, Hyukmin Ha, Borina Kim, Do Hwan Lee, Hojin Dept. of Information Communication Convergence Technology Soongsil University Seoul06978 Korea Republic of School of Electronic Engineering Soongsil University Seoul06978 Korea Republic of Department of Chemical Engineering Hanyang University Seoul04763 Korea Republic of

In this paper, we present an ultra-high resolution organic light-emitting diodes (OLEDs) pixels patterned by conventional photo-lithography via imbuing high chemical and physical resistance to commercial light-emitting polymers through the silicon networked orthogonal gel process. Especially, when silicon networked orthogonal polymers gel layers are pattered by reactive ion etch, a in-situ non-volatile etch-blocking layer (EBL) is formed to prevent pattern distortion or damage. This unique feature not only slows the etch rate but also enhances the anisotropy of etch direction, leading to achieve ultra-high resolution multicolor OPSG-based OLED patterns (up to 4,500 pixels per inch) through photolithography. This patterning strategy is expected to provide a novel paradigm toward ultrahigh-resolution OLED microdisplays. © 2023, John Wiley and Sons Inc. All rights reserved.

关键词： Anisotropy

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Local path planning for multi-robot sytems based on improved artificial potential field algorithm 5

Local path planning for multi-robot sytems based on improved...

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5th IEEE Advanced information Management, Communicates, Electronic and Automation control Conference, IMCEC 2022

作者： Liu, Qiang Liu, Jia Zhao, Ya Shen, Rui Hou, Linlin Zhang, Yunxi School of Automation and Electrical Engineering Tianjin University of Technology and Education Tianjin China Tianjin University of Technology and Education Tianjin Key Laboratory of Information Sensing and Intelligent Control Tianjin China School of Information Science and Engineering Qufu Normal University Rizhao China

ISBN: (纸本)9781665479677

In this paper, the local path planning of mobile robots is studied based on the improved artificial potential field algorithm. The principle of artificial potential field algorithm is explained, and several common shortcomings of traditional artificial potential field algorithm are explained. Accoding to the problem of unreachable target and local minimum in traditional artificial potential field algorithm, the repulsive force function is improved, and the method of resultant force offset is given. Finally, the improved algorithm is simulated in Matalb and compared with the traditional algorithm. Simulation results show that the improved algorithm obtained in this paper is more effective than the traditional algorithm. © 2022 IEEE.

关键词： Multipurpose robots

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