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Hybrid gray wolf optimization-cuckoo search algorithm for RFID network planning

The Journal of China Universities of Posts and Telecommunications 2021年第6期28卷 91-102页

作者： Quan Yixuan Zheng Jiali Xie Xiaode Lin Zihan Luo Wencong School of Computer Electrics and InformationGuangxi UniversityNanning 530004China Guangxi Key Laboratory of Multimedia Communications and Network Technology Guangxi UniversityNanning 530004China

In recent years,with the rapid development of Internet of things(IoT)technology,radio frequency identification(RFID)technology as the core of IoT technology has been paid more and more attention,and RFID network planning(RNP)has become the primary *** with the traditional methods,meta-heuristic method is widely used in *** at the target requirements of RFID,such as fewer readers,covering more tags,reducing the interference between readers and saving costs,this paper proposes a hybrid gray wolf optimization-cuckoo search(GWO-CS)*** method uses the input representation based on random gray wolf search and evaluates the tag density and location to determine the combination performance of the reader's propagation *** with particle swarm optimization(PSO)algorithm,cuckoo search(CS)algorithm and gray wolf optimization(GWO)algorithm under the same experimental conditions,the coverage of GWO-CS is 9.306%higher than that of PSO algorithm,6.963%higher than that of CS algorithm,and 3.488%higher than that of GWO *** results show that the GWO-CS algorithm cannot only improve the global search range,but also improve the local search depth.

关键词： radio frequency identification(RFID) gray wolf optimization(GWO)algorithm cuckoo search(CS)algorithm dynamic adjustment of discovery probability directional mutation

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NL2SQL Enhancement through Semantic Representation Aggregation 5

NL2SQL Enhancement through Semantic Representation Aggregati...

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5th International Conference on computer information Science and Application Technology, CISAT 2022

作者： Long, Lingli Zhu, Yongjin Shao, Jun Kong, Zheng Li, Jian Liu, Zejie Zhang, Xu Jiangsu Frontier Electric Technology Co. Ltd. China School of Computer Science and Engineering Key Laboratory of Computer Network and Information Integration Ministry of Education Southeast University China

ISBN: (纸本)9781510660076

Natural Language to SQL (NL2SQL) is a technology that converts natural language into executable SQL statements. For single table tasks, the dominant approach is a slot-filling-based model which actually performs multi-objective prediction. However, in existing multi-objective models, it is difficult to optimize multiple objectives simultaneously. Low correlation or conflict between various objectives can result in the model not being able to learn the parameters effectively. To effectively address this problem, this paper considers redesigning the sharing mechanism between multiple tasks and the specific network structure of individual tasks through a semantic aggregation approach in order to alleviate the above phenomenon. © 2022 SPIE.

关键词： Semantics

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NL2SQL Generation with Noise Labels based on Multi-task Learning 5

NL2SQL Generation with Noise Labels based on Multi-task Lear...

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2022 5th International Symposium on Big Data and Applied Statistics, ISBDAS 2022

作者： Long, Lingli Zhu, Yongjin Shao, Jun Kong, Zheng Li, Jian Xiang, Yanzheng Zhang, Xu Jiangsu Frontier Electric Technology Co. Ltd. China School of Computer Science and Engineering Key Laboratory of Computer Network and Information Integration Ministry of Education Southeast University China

With the rapid development of artificial intelligence technology, semantic recognition technology is becoming more and more mature, providing the preconditions for the development of natural language to SQL (NL2SQL) technology. In the latest research on NL2SQL, the use of pre-trained models as feature extractors for natural language and table schema has led to a very significant improvement in the effectiveness of the models. However, the current models do not take into account the degradation of the noisy labels on the overall SQL statement generation. It is crucial to reduce the impact of noisy labels on the overall SQL generation task and to maximize the return of accurate answers. To address this issue, we propose a restrictive constraint-based approach to mitigate the impact of noise-labeled labels on other tasks. In addition, parameter sharing approach is used in noiseless-labeled labels to capture each part's correlations and improve the robustness of the model. In addition, we propose to use Kullback-Leibler divergence to constrain the discrepancy between hard and soft constrained coding of noisy labels. Our model is compared with some recent state-of-the-art methods, and experimental results show a significant improvement over the approach in this paper. © Published under licence by IOP Publishing Ltd.

关键词： Semantics

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Calibration Bottleneck: Over-compressed Representations are Less Calibratable 41

Calibration Bottleneck: Over-compressed Representations are ...

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41st International Conference on Machine Learning, ICML 2024

作者： Wang, Deng-Bao Zhang, Min-Ling School of Computer Science and Engineering Southeast University Nanjing China Key Lab. of Computer Network and Information Integration Southeast University MOE China

Although deep neural networks have achieved remarkable success, they often exhibit a significant deficiency in reliable uncertainty calibration. This paper focus on model calibratability, which assesses how amenable a model is to be well recalibrated post-hoc. We find that the widely used weight decay regularizer detrimentally affects model calibratability, subsequently leading to a decline in final calibration performance after post-hoc calibration. To identify the underlying causes leading to poor calibratability, we delve into the calibratability of intermediate features across the hidden layers. We observe a U-shaped trend in the calibratability of intermediate features from the bottom to the top layers, which indicates that over-compression of the top representation layers significantly hinders model calibratability. Based on the observations, this paper introduces a weak classifier hypothesis, i.e., given a weak classification head that has not been over-trained, the representation module can be better learned to produce more calibratable features. Consequently, we propose a progressively layer-peeled training (PLP) method to exploit this hypothesis, thereby enhancing model calibratability. Our comparative experiments show the effectiveness of our method, which improves model calibration and also yields competitive predictive performance. Copyright 2024 by the author(s)

关键词： Deep neural networks

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Changes in nitrogen budget and potential risk to the environment over 20 years(1990–2010) in the agroecosystems of the Haihe Basin, China

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Journal of Environmental Sciences 2015年第2期27卷 195-202页

作者： Mengmeng Zheng Hua Zheng Yingxia Wu Yi Xiao Yihua Du Weihua Xu Fei Lu Xiaoke Wang Zhiyun Ouyang State Key Laboratory of Urban and Regional Ecology Research Center for Eco-Environmental Sciences Chinese Academy of Sciences Wuhan University of Technology Computer Network Information Center Chinese Academy of Sciences

The nitrogen balance can serve as an indicator of the risk to the environment of nitrogen loss from agricultural land. To investigate the temporal and spatial changes in agricultural nitrogen application and its potential threat to the environment of the Haihe Basin in China, we used a database of county-level agricultural statistics to calculate agricultural nitrogen input, output,surplus intensity, and use efficiency. Chemical fertilizer nitrogen input increased by 51.7% from1990 to 2000 and by 37.2% from 2000 to 2010, concomitant with increasing crop ***, the nitrogen surplus intensity increased by 53.5% from 1990 to 2000 and by16.5% from 2000 to 2010, presenting a continuously increased environmental risk. Nitrogen use efficiency decreased from 0.46 in 1990 to 0.42 in 2000 and remained constant at 0.42 in 2010,partly due to fertilizer composition and type improvement. This level indicates that more than half of nitrogen inputs are lost in agroecosystems. Our results suggest that although the improvement in fertilizer composition and types has partially offset the decrease in nitrogen use efficiency, the environmental risk has still increased gradually over the past 20 years, along with the increase in crop yields and nitrogen application. It is important to achieve a better nitrogen balance through more effective management to significantly reduce the environmental risk,decrease nitrogen surplus intensity, and increase nitrogen use efficiency without sacrificing crop yields.

关键词： Nitrogen budget Nitrogen surplus intensity Nitrogen use efficiency Environmental risk Agroecosystem Haihe Basin

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Temporally or spatially dispersed joint RFID estimation using snapshots of variable lengths 15

Temporally or spatially dispersed joint RFID estimation usin...

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16th ACM International Symposium on Mobile Ad Hoc networking and Computing, MobiHoc 2015

作者： Xiao, Qingjun Chen, Min Chen, Shigang Zhou, Yian Key Lab of Computer Network and Information Integration Southeast University Ministry of Education China Department of Computer and Information Science and Engineering University of Florida GainesvilleFL United States

ISBN: (纸本)9781450334891

Radio-frequency identification (RFID) technology has been widely used in applications such as inventory control, object tracking, supply chain management. An important research is to estimate the number of tags in a certain area covered by readers. This paper extends the research in both temporal and spatial dimensions to provide much richer information for monitoring the dynamics of distributed RFID systems. More specifically, we are interested in estimating the joint properties of any two snapshots taken at arbitrary locations and arbitrary times in a system. With many practical applications, there is however little prior work on this problem. We propose a joint RFID estimation protocol based on a simple yet versatile snapshot construction. Given the snapshots of any two tag sets, although their sizes may be very different, we design a way to combine their information and more importantly derive formulas to extract the joint properties of the two tag sets from the combined information, with an accuracy that can be arbitrarily set. Through formal analysis, we determine the optimal system parameters that minimize the execution time of taking snapshots, under the constraints of a given accuracy requirement. Our simulation results show that the proposed protocol can reduce the execution time by multifold when comparing with the best alternative approach in the literature. Copyright © 2015 ACM.

关键词： Inventory control

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A feedback-based timeout packets dropping strategy in real-time wireless sensor networks

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2nd World Congress on computer Science and information Engineering, CSIE 2011

作者： Shen, Zhuowei Xu, Peng Xu, Xiaoxi Key Lab. of Computer Network and Information Integration Ministry of Education School of Computer Sci. and Eng. Southeast University Nanjing China

ISBN: (纸本)9783642257681

Resource limited real-time wireless sensor network is a new type of application of sensor network. In this kind of networks, there are numerous invalid real-time packets, which have already expired or are destined to expire. In this paper, a feedback-based timeout packet dropping strategy (FBTPD) is proposed. With this strategy, timestamps are piggybacked in real-time packets. So that sink node can gather the historical information and estimate the future transmitting time of some sensor node. Then the estimated transmitting time is fed back to the sensor node in a feedback packet. The sensor node hereby drops the invalid realtime packets which will expire later. Simulation experiments reveal that: compared with other dropping policies, FBTPD can drop more invalid real-time packets, and can significantly improve the throughput of the non real-time packets. Thus FBTPD can efficiently boost the resources utilization in wireless sensor networks, especially in hybrid real-time wireless sensor networks. © Springer-Verlag Berlin Heidelberg 2012.

关键词： Real time systems

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An effective heuristic for on-line tenant placement problem in SaaS

An effective heuristic for on-line tenant placement problem ...

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2010 IEEE 8th International Conference on Web Services, ICWS 2010

作者： Zhang, Yi Wang, Zhihu Gao, Bo Guo, Changjie Sun, Wei Li, Xiaoping School of Computer Science and Engineering Southeast University 210096 Nanjing China Key Laboratory of Computer Network and Information Integration Ministry of Education China IBM Research-China 100096 Beijing China

ISBN: (纸本)9780769541280

As one of the key characteristics of Software as a Service (SaaS), multi-tenancy aims to support massive customers by sharing application instances and databases. To achieve the high economies of scale, one of the most issues needing to be solved in the real industry is that, given a fixed number of nodes, how to optimally place on-boarding tenants to maximize the total supported number of tenants without violating their SLA requirements. This paper focuses on this problem, which is called On-line Tenant Placement Problem (OTPP). In order to calculate the resource consumption of onboarding tenants, a novel resource consumption estimation model for multi-tenant pattern is proposed in this paper. Based on this model, we explore the complexity of OTPP. A robust heuristic is proposed for the OTPP. The simulation experimental results show the high effectiveness and the good efficiency of our algorithm. © 2010 IEEE.

关键词： Application programs

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Barrier Offset Varying-Parameter Dynamic Learning network for Solving Dual-Arms Human-Like Behavior Generation

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IEEE Transactions on Cognitive and Developmental Systems 2025年

作者： Zhang, Zhijun Zhang, Mingyang Guo, Jinjia He, Haotian School of Automation Science and Engineering South China University of Technology Guangzhou510640 China Key Library of Autonomous Systems and Network Control Ministry of Education China Jiangxi Thousand Talents Plan Nanchang University Nanchang330031 China Guangzhou510335 China Shaanxi Provincial Key Laboratory of Industrial Automation School of Mechanical Engineering Shanxi University of Technology Hanzhong723001 China School of Information Science and Engineering Changsha Normal University Changsha410100 China School of Automation Science and Engineering Institute of Artificial Intelligence and Automation Guangdong University of Petrochemical Technology Maoming525000 China School of Computer Science and Engineering Jishou University Jishou416000 China

Enabling robots to imitate human actions and perform tasks with high precision while avoiding potential obstacles in the environment can effectively enhance the interaction between social robots and humans. In this paper, to achieve higher precision trajectory tracking and obstacle avoidance for dual-arm humanoid robots, the barrier offset varying-parameter dynamic learning neural (BOVDL) network method is proposed and applied to dual-arm humanoid behavior generation scheme. To do so, a dual-arms humanoid robot model is set up, and transformed into a constrained time-varying quadratic programming (TVQP) problem. Secondly, by using lagrangian multiplier method and Karush-Kuhn-Tuchker condition, the inequality constrained TVQP is converted as a time-varying equation with a barrier parameter. Thirdly, a varying-parameter dynamic learning network is presented to solve the time-varying equation with a barrier parameter. computer simulation experiments are conducted to verify the feasibility, accuracy, and safety of the proposed BOVDL network method. Experimental results show that all 14 joints of the humanoid robot's arms are within the motion range of each real human arm's physical constraints. The maximum position error and velocity error between the desired trajectory and the actual trajectory of the end effector are less than 10-6m magnitude and 10-7m magnitude, respectively, representing a reduction of 5 orders of magnitude compared to the traditional varying-parameter convergent-differential neural network. Furthermore, the proposed method also enables the dual-arm humanoid robot to avoid collisions with obstacles while performing tasks, demonstrating the superiority of the proposed BOVDL network scheme. © 2016 IEEE.

关键词： Anthropomorphic robots

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CARRIAGE: Fault tolerant CORBA system based on portable interceptors 2

CARRIAGE: Fault tolerant CORBA system based on portable inte...

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2nd International Workshop on Autonomous Decentralized System

作者： Zhang, Y Shen, ZW Wang, Y Department of Computer Science and Engineering The Key laboratory of Computer Network and Information Integrity Ministry of Education South-East University China

ISBN: (纸本)0780376242

Fault Tolerance requirement, which demands the reliability and consistency in compute systems, becomes a hot issue in current distributed object application field. Based on standardized Portable Interceptors mechanism, CARRIAGE system has successfully integrated ORB US, a CORBA implementation developed by the authors and EDEN, a fault-tolerant framework into a whole new Fault Tolerant CORBA system, which uses active replication style to enhance fault tolerance service in CORBA domain with low cost and high efficiency. Practice has identified that this software prototype conforms to the standard specification thoroughly and provides a feasible and convenient way to glue the legacy systems without modifying the original systems or the application programs either.

关键词： software reliability fault tolerant computing distributed object management software portability CARRIAGE fault tolerant CORBA system portable interceptors distributed object application ORBUS CORBA EDEN fault-tolerant framework active replication style software prototype legacy systems

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