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Traffic engineering in Dynamic Hybrid Segment Routing Networks

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Computers, Materials & Continua 2021年第7期68卷 655-670页

作者： Yingya Guo Kai Huang Cheng Hu Jiangyuan Yao Siyu Zhou College of Mathematics and Computer Science Fuzhou UniversityFuzhou350000China Fujian Key Laboratory of Network Computing and Intelligent Information Processing Fuzhou UniversityFuzhou350000China Key Laboratory of Spatial Data Mining&Information Sharing Ministry of EducationFuzhou350003China School of Information Science and Technology Guangdong University of Foreign StudiesGuangzhou510006China School of Computer Science and Cyberspace Security Hainan UniversityHaiKou570228China Tandon School of Engineering New York UniversityNew York10012USA Department of Computing Hong Kong Polytechnic UniversityHong Hom999077Hong Kong

The emergence of Segment Routing(SR)provides a novel routing paradigm that uses a routing technique called source packet *** SR architecture,the paths that the packets choose to route on are indicated at the ingress *** with shortest-path-based routing in traditional distributed routing protocols,SR can realize a flexible routing by implementing an arbitrary flow splitting at the ingress *** the advantages of SR,it may be difficult to update the existing IP network to a full SR deployed network,for economical and technical *** partial of the traditional IP network to the SR network,thus forming a hybrid SR network,is a preferable *** the traffic is dynamically changing in a daily time,in this paper,we propose a Weight Adjustment algorithm WASAR to optimize routing in a dynamic hybrid SR *** algorithm can be divided into three steps:firstly,representative Traffic Matrices(TMs)and the expected TM are obtained from the historical TMs through ultrascalable spectral clustering ***,given the network topology,the initial network weight setting and the expected TM,we can realize the link weight optimization and SR node deployment optimization through a Deep Reinforcement Learning(DRL)***,we optimize the flow splitting ratios of SR nodes in a centralized online manner under dynamic traffic demands,in order to improve the network *** the evaluation,we exploit historical TMs to test the performance of the obtained routing configuration in *** extensive experimental results validate that our proposed WASAR algorithm has superior performance in reducing Maximum Link Utilization(MLU)under the dynamic traffic.

关键词： Traffic engineering routing optimization segment routing deep reinforcement learning ultra-scalable spectral clustering

Types and Evolutionary Boundaries of Agents

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Types and Evolutionary Boundaries of Agents

Artificial Intelligence Technology (ACAIT), Asian Conference on

作者： Feng Liu Ying Liu The Key Laboratory of Big Data Mining and Knowledge Management Chinese Academy of Sciences Research Center on Fictitious Economy and Data Science the Chinese Academy of Sciences Beijing China School of Economics and Management University of Chinese Academy of Sciences Beijing China

ISBN: (纸本)9781665426312

Through the analysis of the characteristics of natural intelligent systems, the three laws of intelligence are exploringly proposed. The most important point is that any agent is a system with knowledge input, output, (dynamic) storage and creation abilities Since an agent has four abilities, and each ability has three states, including zero, infinity, and finite (between zero and infinity), 81 types of agents can be formed. Therefore, it can be inferred that Alpha point (No. 1), where all the four abilities of an agent are zero, and Omega point (No. 81), where all four abilities are infinite are the boundary of the evolution of Agent. This paper designs experiments to detect these 81 agents, and finds that 11 of them can be confirmed by experiments at present. Through the discussion of the states of Agents No. 64 to No. 81, fresh thinking is proposed for the generation and realization of the paradox.

关键词： Intelligent systems

New entanglement-assisted quantum codes from negacyclic codes

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arXiv 2023年

作者： Chen, Xiaojing Lu, Xingbo Zhu, Shixin Jiang, Wan Wang, Xindi School of Internet Anhui University Anhui Hefei230039 China School of Mathematics Hefei University of Technology Anhui Hefei230601 China Key Laboratory of Knowledge Engineering with Big Data Ministry of Education Hefei University of Technology Anhui Hefei230601 China School of Computer and Information Hefei University of Technology Anhui Hefei230601 China

The theory of entanglement-assisted quantum error-correcting codes (EAQECCs) is a generalization of the standard stabilizer quantum error-correcting codes, which can be possibly constructed from any classical codes by relaxing the duality condition and utilizing preshared entanglement between the sender and receiver. In this paper, a new family of EAQECCs is constructed from negacyclic codes of length n = q2a+1, where q is an odd prime power, a = m22+1 and m is an odd integer. Some new entanglement-assisted quantum maximum distance separable (EAQMDS) codes are obtained in the sense that their parameters are not covered by the previously known ones. Copyright © 2023, The Authors. All rights reserved.

关键词： Quantum entanglement

Collaborative innovation community capacity building for electronic records security management 17

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Collaborative innovation community capacity building for ele...

17th International Conference on Intellectual Capital, knowledge Management and Organisational Learning, ICICKM 2020

作者： Wang, Lili An, Xiaomi Xu, Jicang Huang, Jie Guo, Mingjun Hu, Jufang School of Information Resource Management Renmin University of China Beijing China Key Laboratory of Data Engineering and Knowledge Engineering Renmin University of China Beijing China Renmin University of China Libraries Beijing China

ISBN: (纸本)9781912764723

With more and more governmental business going digital and collaborative to the best of whole government value and public value, electronic records security management (ERSM) faces great challenges. There is a growing understanding that standardization is the key to the successful ERSM, when governmental business requires cross-boundary collaboration. However, previous studies of collaborative innovation community capacity building (CICCB) on ERSM are mainly from the perspective of archival study to the best of long term preservation of electronic archives,with little concerns about needs of different interested parties. Few studies have been taken from interdisciplinary perspective and integrated use of international standards of business continuity management, records management, knowledge management and information security management to the best value of knowledge sharing and continuity of business, records, knowledge and security service. Based on prior findings and the integrated use of ISO management systems standards (ISO/IEC 27001, 2013;ISO 15489-1, 2016;ISO 30401, 2018;ISO 22301, 2019;ISO 30301, 2019), this study analyses the motivation mechanisms of CICCB for ERSM, then develops an extended conceptual framework for CICCB, including cognitive collaboration which means shared knowledge and values on ERSM for all types of interested parties that enable continual improvement;interested parties collaboration which means human interactions on shared rules for community practice on ERSM that enable improved transparency and accountability;process collaboration which means shared standards, guidelines and models for whole process control that enable electronic records controllable with characteristics of authenticity, reliability, integrity, usability, confidentiality and availability;technical collaboration which means shared solutions that enable electronic records systems reliable, secure, compliant, comprehensive, systematic. The above collaborations need com

关键词： knowledge management

Long-Term Influence of Air Pollutants on Morbidity and All-Cause Mortality of Cardiometabolic Multi-Morbidity: A Cohort Analysis of the UK Biobank Participants

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SSRN

SSRN 2023年

作者： Jiang, Zhou Zhang, Shuo Cheng, keying Wu, Yuxuan Zeng, Ping Wang, Ting Department of Biostatistics School of Public Health Xuzhou Medical University Jiangsu Xuzhou221004 China Center for Medical Statistics and Data Analysis Xuzhou Medical University Jiangsu Xuzhou221004 China Key Laboratory of Human Genetics and Environmental Medicine Xuzhou Medical University Jiangsu Xuzhou221004 China Key Laboratory of Environment and Health Xuzhou Medical University Jiangsu Xuzhou221004 China Engineering Research Innovation Center of Biological Data Mining and Healthcare Transformation Xuzhou Medical University Jiangsu Xuzhou221004 China

Background: The associations of air pollutants with cardiometabolic diseases (CMDs) have been widely studied, whereas the relations with cardiometabolic multi-morbidity (CMM) were less ***: We aimed to employ the UK Biobank cohort (N=317,160) to study the association between six air pollutants (PM2.5, PM10, PM2.5-10, PM2.5abs, NO2, and NOx) and four CMDs including type II diabetes (T2D), coronary artery disease (CAD), stroke and hypertension. CMM was defined as occurrence of two or more of the above four diseases. Multi-state Cox models were performed to estimate hazard ratio (HR) and its 95% confidence interval (95%CI).Results: During a median follow-up of 12.8 years, 52,211 participants developed only one CMD, 15,446 further developed CMM, and 16,861 ultimately died. It was demonstrated that per interquartile range increase (IQR) increases in PM2.5, PM10, PM2.5-10, PM2.5abs, NO2, and NOx would increase 12% (9~15%), 4% (1~7%), 3% (1~6%), 7% (4~10%), 11% (8~15%) and 10% (7~13%) higher risk of developing one CMD from health baseline;7% (2~12%), 8% (3~13%), 6% (2~11%), 10% (5~15%), 13% (7~18%) and 10% (5~15%) greater risk of occurring CMM from one CMD baseline;and 11% (-2~26%), 22% (7~38%), 17% (3~32%), 31% (16~49%), 33% (17~51%) and 32% (17~50%) larger risk of causing death from CMM baseline, ***: We revealed that people living in areas with high air pollution suffered from higher hazard of CMD, CMM and all-cause mortality, and that keeping clean air was an effective approach to prevent or mitigate initiation, progression, and death from healthy to CMDs and from CMDs to CMM. © 2023, The Authors. All rights reserved.

关键词： Diseases

Generative AI for Deep Reinforcement Learning: Framework, Analysis, and Use Cases

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arXiv 2024年

作者： Sun, Geng Xie, Wenwen Niyato, Dusit Mei, Fang Kang, Jiawen Du, Hongyang Mao, Shiwen College of Computer Science and Technology Jilin University Changchun130012 China Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education Jilin University Changchun130012 China College of Computing and Data Science Nanyang Technological University Singapore639798 Singapore School of Automation Guangdong University of Technology Guangzhou510006 China Department of Electrical and Electronic Engineering The University of Hong Kong 999077 Hong Kong Department of Electrical and Computer Engineering Auburn University Auburn36830 United States

As a form of artificial intelligence (AI) technology based on interactive learning, deep reinforcement learning (DRL) has been widely applied across various fields and has achieved remarkable accomplishments. However, DRL faces certain limitations, including low sample efficiency and poor generalization. Therefore, we present how to leverage generative AI (GAI) to address these issues above and enhance the performance of DRL algorithms in this paper. We first introduce several classic GAI and DRL algorithms and demonstrate the applications of GAI-enhanced DRL algorithms. Then, we discuss how to use GAI to improve DRL algorithms from the data and policy perspectives. Subsequently, we introduce a framework that demonstrates an actual and novel integration of GAI with DRL, i.e., GAI-enhanced DRL. Additionally, we provide a case study of the framework on UAV-assisted integrated near-field/far-field communication to validate the performance of the proposed framework. Moreover, we present several future directions. Finally, the related code is available at: https://***/GAI-enhanced-DRL. Copyright © 2024, The Authors. All rights reserved.

关键词： Deep reinforcement learning

Perceptive self-supervised learning network for noisy image watermark removal

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arXiv 2024年

作者： Tian, Chunwei Zheng, Menghua Li, Bo Zhang, Yanning Zhang, Shichao Zhang, David School of Software Northwestern Polytechnical University Xi’an710129 China National Engineering Laboratory for Integrated Aero-Space-Ground-Ocean Big Data Application Technology Xi’an710129 China School of Electronics and Information Northwestern Polytechnical University Xi’an710129 China School of Computer Science Northwestern Polytechnical University National Engineering Laboratory for Integrated AeroSpace-Ground-Ocean Big Data Application Technology Xi’an710129 China Guangxi Key Lab of Multisource Information Mining & Security College of Computer Science & Engineering Guangxi Normal University Guilin541004 China Shenzhen518172 China Shenzhen Institute of Artificial Intelligence and Robotics for Society Shenzhen518172 China

Popular methods usually use a degradation model in a supervised way to learn a watermark removal model. However, it is true that reference images are difficult to obtain in the real world, as well as collected images by cameras suffer from noise. To overcome these drawbacks, we propose a perceptive self-supervised learning network for noisy image watermark removal (PSLNet) in this paper. PSLNet depends on a parallel network to remove noise and watermarks. The upper network uses task decomposition ideas to remove noise and watermarks in sequence. The lower network utilizes the degradation model idea to simultaneously remove noise and watermarks. Specifically, mentioned paired watermark images are obtained in a self-supervised way, and paired noisy images (i.e., noisy and reference images) are obtained in a supervised way. To enhance the clarity of obtained images, interacting two sub-networks and fusing obtained clean images are used to improve the effects of image watermark removal in terms of structural information and pixel enhancement. Taking into texture information account, a mixed loss uses obtained images and features to achieve a robust model of noisy image watermark removal. Comprehensive experiments show that our proposed method is very effective in comparison with popular convolutional neural networks (CNNs) for noisy image watermark removal. Codes can be obtained at https://***/hellloxiaotian/PSLNet. Copyright © 2024, The Authors. All rights reserved.

关键词： Image denoising

Listening to the user's voice: A temporal analysis of autism-related questions on Quora

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Proceedings of the Association for Information Science and Technology 2019年第1期56卷 513-516页

作者： Zhao, Yuehua Min, Chao Han, Xu Deng, Sanhong Wang, Hao Li, Jiang Nanjing University Jiangsu Key Laboratory of Data Engineering and Knowledge Service Nanjing China Nanjing University Nanjing China

Social question and answer (Q&A) platforms offer a new way for identifying information needs of people with certain diseases. Taking Quora as an example, we examine which health topics are of interest to autistic people and how these topics evolve over time. Experimental results reveal increasingly heavy and diverse attention to the condition, from diagnosis and treatment of autism itself to extended issues like social challenges, parenting, and education issues. We find that users tend to post clinical concerns about autism on Quora although traditionally such social Q&A platforms encourage more social and awareness-level questions. New concerns have appeared recently about autism's relations to other diseases like attention deficit hyperactivity disorder (ADHD) and obsessive–compulsive disorder (OCD). This study is beneficial for tracking and responding to autistic patients' and caregivers' information needs. Author(s) retain copyright, but ASIS&T receives an exclusive publication license

关键词： Diseases

Roller-Quadrotor: A Novel Hybrid Terrestrial/Aerial Quadrotor with Unicycle-Driven and Rotor-Assisted Turning

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arXiv 2023年

作者： Zheng, Zhi Wang, Jin Wu, Yuze Cai, Qifeng Yu, Huan Zhang, Ruibin Tu, Jie Meng, Jun Lu, Guodong Gao, Fei The State Key Laboratory of Fluid Power and Mechatronic Systems School of Mechanical Engineering Zhejiang University Hangzhou310027 China Robotics Institute of Zhejiang University Hangzhou310027 China Robotics Research Center of Yuyao City Ningbo315400 China The State Key Laboratory of Industrial Control Technology Zhejiang University Hangzhou310027 China Huzhou Institute of Zhejiang University Huzhou313000 China Center for Data Mining and Systems Biology College of Electrical Engineering Zhejiang University Hangzhou310027 China

The Roller-Quadrotor is a novel quadrotor that combines the maneuverability of aerial drones with the endurance of ground vehicles. This work focuses on the design, modeling, and experimental validation of the Roller-Quadrotor. Flight capabilities are achieved through a quadrotor configuration, with four thrust-providing actuators. Additionally, rolling motion is facilitated by a unicycle-driven and rotor-assisted turning structure. By utilizing terrestrial locomotion, the vehicle can overcome rolling and turning resistance, thereby conserving energy compared to its flight mode. This innovative approach not only tackles the inherent challenges of traditional rotorcraft but also enables the vehicle to navigate through narrow gaps and overcome obstacles by taking advantage of its aerial mobility. We develop comprehensive models and controllers for the Roller-Quadrotor and validate their performance through experiments. The results demonstrate its seamless transition between aerial and terrestrial locomotion, as well as its ability to safely navigate through gaps half the size of its diameter. Moreover, the terrestrial range of the vehicle is approximately 2.8 times greater, while the operating time is about 41.2 times longer compared to its aerial capabilities. These findings underscore the feasibility and effectiveness of the proposed structure and control mechanisms for efficient navigation through challenging terrains while conserving energy. Copyright © 2023, The Authors. All rights reserved.

关键词： Antennas