检索结果-内蒙古大学图书馆

Effects of Combined Stress from Salt and Herbicide on Microbial Remediation of Soil Contaminated by n-Hexadecane and Phenanthrene

引用

China Petroleum Processing & Petrochemical Technology 2022年第2期24卷 126-137页

作者： Liu Bingkun Zuo Shuai Wang Ruirui Dong Kangning Zhang Xiuxia Li Ruyue Hao Boyu Li Jing Yin Linghao Bai Yuhao Song Jiayu Gu Yingying Sun Juan State Key Laboratory of Petroleum Pollution Control Beijing 102206 Department of Environment and Safety Engineering China University of PetroleumQingdao 266580 Department of Computer Science and Technology China University of PetroleumQingdao 266580

In this study,physicochemical,cluster,and high-throughput sequencing analyses were used to investigate the joint effects of salt and herbicide(glyphosate)stress factors on the microbial remediation of soil contaminated by n-hexadecane and *** on the soil’s physical and chemical properties,differences in microbial quantity and enzyme activities were analyzed among the samples,and how that influenced distribution of soil community structure was focused *** 120 days of indoor simulated remediation,the cumulative degradation rate of n-hexadecane decreased by 94.92%(blank control),96.96%(low concentration salt and glyphosate stress group),65.07%(high concentration salt and glyphosate stress group),while that of phenanthrene decreased by 87.33%(blank control),86.25%(low concentration salt and glyphosate stress group),58.45%(high concentration salt and glyphosate stress group).The combined stress of salt and herbicides was capable of lowering the reduction efficiency of organic matter,total nitrogen,and total phosphorus,and also restricting the growth of microorganisms and enzyme *** analysis results indicated that the non-stress group was similar to the low-concentration compound stress group during different remedial period,whereas both of those differed starkly from the high-concentration compound stress ***-throughput sequencing revealed that the dominant soil bacteria phyla shifted from Firmicutes to Actinobacteria within 120 days of remediation.

关键词： oil-contaminated soil cluster analysis common quantity sequencing microorganisms salt stress glyphosate stress

来源：评论

学校读者我要写书评

暂无评论

Decentralised Collaborative Iterative Learning control for Multi-Agent Systems Point-to-Point Channel Tracking

Decentralised Collaborative Iterative Learning Control for M...

引用

American control Conference (ACC)

作者： Shangcheng Chen Christopher T. Freeman School of Automatic Control and Systems Engineering University of Sheffield School of Electronics and Computer Science University of Southampton

ISBN: (数字)9798350382655

ISBN: (纸本)9798350382662

Application of learning to collaborative tracking control of multi-agent systems has addressed a wealth of problems across transportation, manufacturing, rescue, aerospace and medical care areas. Iterative learning control algorithms have been proposed to address synergistic objectives in general optimization problems, achieving a transparent balance between convergence speed, tracking error and robustness. This paper builds on this framework by formulating a point-to-point strategy that allows each subsystem to track only a portion of the trajectory, thereby providing a more flexible design framework with broad utility. Moreover, a channel tracking strategy is developed to ensure that the total output during untracked intervals is limited to an a specified range. The practicality of this novel control framework is illustrated through derivation, simulation and evaluation of three new iterative learning laws: inverse, gradient and norm-optimal. Convergence analysis for the proposed framework is also given.

关键词： Collaboration Transportation Medical services Robustness Trajectory Manufacturing Optimization

来源：评论

学校读者我要写书评

暂无评论

An Abstract Interpretation-Based Framework for WCET Analysis of Parallel Programs

An Abstract Interpretation-Based Framework for WCET Analysis...

引用

IEEE International Conference on Networking, Sensing and control

作者： Xinbang Hu Guanjun Liu Xiaofeng Li Kaiwen Zhang Jian Guan Bin Gu Department of Computer Science Tongji University Shanghai China Beijing Institute of Control Engineering Beijing China

ISBN: (数字)9798350365221

ISBN: (纸本)9798350365238

Estimating the Worst-Case Execution Time (WCET) of programs in an embedded multi-core environment is fundamental for schedulability analysis. In this paper, we propose a framework for calculating the WCET of programs originally designed for single-core systems when migrated to and executed in parallel on multi-core environments. First, we decompose single-core tasks and convert them into parallel programs using OpenMP. Our approach extends the task dependency graph to describe relevant information for parallel tasks (such as execution time estimation, core allocation, and inter-task dependencies). Finally, we present an iterative algorithm based on abstract interpretation. This algorithm takes the parallel task dependency graph as input and uses fixed-point analysis to determine the WCET of parallel programs. We conducted experiments on a physical machine to verify the feasibility of our solution.

关键词： Runtime Program processors Multicore processing Estimation Parallel processing Benchmark testing Real-time systems Sensors Iterative methods Resource management

来源：评论

学校读者我要写书评

暂无评论

Adversarial Training with Maximal Coding Rate Reduction

Adversarial Training with Maximal Coding Rate Reduction

引用

Asilomar Conference on Signals, Systems & computers

作者： Hsiang-Yu Chu Hongbo Zhao Markus Flierl Electrical Engineering and Computer Science KTH Royal Institute of Technology Stockholm Sweden Department of Control Science and Engineering Harbin Institute of Technology Harbin China

ISBN: (数字)9798350354058

ISBN: (纸本)9798350354065

Deep convolutional networks can solve various complex tasks in the field of image processing. However, adversarial attacks have been shown to have the ability of fooling deep learning models. Adversarial training is one commonly used strategy to improve the robustness of deep learning models against adversarial examples, which is performed by incorporating adversarial examples into the training process. Traditionally, during this process, cross-entropy loss is used as the loss function. In order to improve the robustness of deep learning models against adversarial examples, we propose in this paper two new methods of adversarial training by applying the principle of Maximal Coding Rate Reduction (MCR 2 ). We evaluate the performance of different adversarial training methods by comparing the clean accuracy and adversarial accuracy. It is shown that adversarial training with the MCR 2 loss function yields a more robust network than the traditional adversarial training method. In our experiments, adversarial accuracies are improved by up to 10%. The two loss functions are discussed by using a model.

关键词： Training Deep learning Hands Accuracy Image coding Computational modeling Robustness Data models Encoding Convolutional neural networks

来源：评论

学校读者我要写书评

暂无评论

Deformable Feature Alignment and Refinement for Moving Infrared Dim-small Target Detection

arXiv

引用

arXiv 2024年

作者： Luo, Dengyan Xiang, Yanping Wang, Hu Ji, Luping Li, Shuai Ye, Mao School of Computer Science and Engineering University of Electronic Science and Technology of China Chengdu611731 China School of Control Science and Engineering Shandong University Jinan250000 China

The detection of moving infrared dim-small targets has been a challenging and prevalent research topic. The current state-of-the-art methods are mainly based on ConvLSTM to aggregate information from adjacent frames to facilitate the detection of the current frame. However, these methods implicitly utilize motion information only in the training stage and fail to explicitly explore motion compensation, resulting in poor performance in the case of a video sequence including large motion. In this paper, we propose a Deformable Feature Alignment and Refinement (DFAR) method based on deformable convolution to explicitly use motion context in both the training and inference stages. Specifically, a Temporal Deformable Alignment (TDA) module based on the designed Dilated Convolution Attention Fusion (DCAF) block is developed to explicitly align the adjacent frames with the current frame at the feature level. Then, the feature refinement module adaptively fuses the aligned features and further aggregates useful spatio-temporal information by means of the proposed Attention-guided Deformable Fusion (AGDF) block. In addition, to improve the alignment of adjacent frames with the current frame, we extend the traditional loss function by introducing a new motion compensation loss. Extensive experimental results demonstrate that the proposed DFAR method achieves the state-of-the-art performance on two benchmark datasets including DAUB and IRDST. Copyright © 2024, The Authors. All rights reserved.

关键词： Convolution

来源：评论

学校读者我要写书评

暂无评论

Digital Twin System Based on NoSQL Database 1

引用

TEPEN International Workshop on Fault Diagnostics and Prognostics, TEPEN-IWFDP 2024

作者： Weng, Feiyang Wang, Hongjun Jiang, Fan Fu, Mingzhu Cui, Yanyan Ma, Zeyu School of Computer Science Beijing University of Information Science and Technology Beijing102206 China School of Information Management Beijing University of Information Science and Technology Beijing102206 China School of Mechanical Engineering Beijing University of Information Science and Technology Beijing102206 China Beijing International Science Cooperation Base of High-End Equipment Intelligent Perception and Control Beijing100192 China

ISBN: (数字)9783031694837

ISBN: (纸本)9783031694820

With the rapid development of digital twin technology in the industrial field, there is an increasing demand for complex data management and real-time processing functions. This paper explores the application of non-relational databases in digital twin modelling and demonstrates their advantages over traditional relational databases through a case study of an electronic component assembly workshop. The study first describes the key characteristics of non-relational databases, including their flexibility, scalability, and ability to handle big data efficiently, which make them ideal for supporting digital twin models. The paper then proposes a framework for a digital twin model based on non-relational databases, detailing how the framework exploits the features of non-relational databases for efficient data synchronization, storage and analysis. By applying the model to an electronic component assembly shop and comparing it with a traditional relational database-based solution, the results show that the non-relational database-based model has significant advantages in terms of data processing efficiency, system response time, and scalability. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.

关键词： Smart manufacturing

来源：评论

学校读者我要写书评

暂无评论

Secure Recursive State Estimation of Networked Systems Against Eavesdropping: A Partial-Encryption-Decryption Method

引用

IEEE Transactions on Automatic control 2024年第6期70卷 3681-3694页

作者： Zou, Lei Wang, Zidong Shen, Bo Dong, Hongli Donghua University College of Information Science and Technology Engineering Research Center of Digitalized Textile and Fashion Technology Ministry of Education Shanghai201620 China Brunel University London Department of Computer Science UxbridgeUB8 3PH United Kingdom Northeast Petroleum University Artificial Intelligence Energy Research Institute Heilongjiang Provincial Key Laboratory of Networking and Intelligent Control Daqing163318 China

This paper addresses the problem of secure recursive state estimation for a networked linear system, which may be vulnerable to interception of transmitted measurement data by eavesdroppers. To effectively protect information security, an encryption-decryption-based communication scheme can be used, but encrypting all the measurement data from sensors can result in significant computational costs. To address this issue, a partial-encryption-decryption (PED) mechanism is proposed to enhance information security with relatively low computational costs. In this mechanism, only part of the transmitted measurement signals are encrypted, and the remaining signals are transmitted directly to the estimator. A Jordan-canonical-form-based approach is developed to select the appropriate parameter for the PED mechanism, and recursive formulas for the state estimator are designed based on the principle of minimum mean squared error. Sufficient conditions are derived to guarantee the ultimate boundedness of the estimation error variance matrix. Finally, the proposed PED-based recursive state estimation scheme is evaluated through two simulation examples to demonstrate its effectiveness. © 1963-2012 IEEE.

关键词： Mean square error

来源：评论

学校读者我要写书评

暂无评论

An Efficient Hybrid Red Panda Optimization-Similarity-Navigated Graph Neural Network with Blockchain Technology for Shared Electric Vehicle Charging 4

An Efficient Hybrid Red Panda Optimization-Similarity-Naviga...

引用

4th International Conference on Sustainable Expert Systems, ICSES 2024

作者： Sammy, F. Rajeshwari, S. Prashanth, G.K. Thirumalaimuthu, Babu Pokhariya, Hemant Singh Natrayan, L. Koneru Lakshmaiah Education Foundation Department of Computer Science and Engineering Andhra Pradesh Vaddeswaram522 302 India Bangalore Institute of Technology Department of Mathematics Karnataka Bengaluru560004 India Siddaganga Institute Technology Department of Mca Karnataka Tumkur-572103 India St. Joseph's College of Engineering Department of Instrumentation and Control Engineering Tamil Nandu Chennai600119 India Graphic Era Deemed to be University Department of Computer Science & Engineering Uttarakhand Dehradun248002 India Saveetha School of Engineering Simats Department of Mechanical Engineering Tamil Nadu Chennai602105 India

ISBN: (纸本)9798331540364

Blockchain technology for shared electric vehicle (EV) charging makes use of a distributed ledger in handling different transactions which promotes authenticity in charging. However, this technology can be non-scalable at times which slows down the transaction rates as the scale increases in an organization and may also demand high computational as well as energy requirements which increases the inefficiency of the total system, the operating expenses of EV charging station, costs of energy utilized for charging, cost of maintenance and cost of station infrastructure may prove to be a weakness, impacting the feasibility of infrastructure deployment and upkeep expenses of the charging stations. To overcome these drawbacks, this paper proposes a hybrid method for blockchain technology with shared EV charging. The proposed approach combines the use of the Red Panda Optimization (RPO) with Similarity-Navigated Graph Neural Network (SNGNN). Hence, it is named as hybrid RPO-SNGNN approach. Reducing the operating cost of EV charging position and maximizes the security efficiency is the main aim of the proposed approach. To optimize scheduling and resource allocation by finding efficient paths by RPO and predict future demand and user behaviour patterns by SNGNN. By then, the proposed model has been put into practice on the MATLAB work platform and contrasted with other existing methods. The proposed technique outperforms all existing techniques, including Fuzzy-based Cross Hierarchical Reinforcement Q Learning (FCHRQL), Non-Dominated Sorting Genetic Algorithm-Long Short-Term Memory Network (NSGA-II-LSTMN), and Ant Colony Optimization-Proximal Policy Optimization (ACO-PPO). The proposed method shows the operating cost of $550 and the security rate is 97%. From the result, the proposed approach operating cost is low and the security rate is high when compared to the existing approaches. © 2024 IEEE.

关键词： Charging stations

来源：评论

学校读者我要写书评

暂无评论

Adaptive Particle Swarm Optimization of U-net Parameters for Marine Aquaculture Image Segmentation

Adaptive Particle Swarm Optimization of U-net Parameters for...

引用

International Conference on Intelligent control and Information Processing (ICICIP)

作者： Jin Zhao Jun Wang Min Han Jianchao Fan School of Computer Science and Engineering Chongqing Three Gorges University Chongqing China Department of Computer Science and Department of Data Science City University of Hong Kong Hong Kong School of Control Science and Engineering Dalian University of Technology Dalian China

ISBN: (数字)9798331516147

ISBN: (纸本)9798331516154

Marine aquaculture image segmentation plays a crucial role in managing aquatic resources and environmental protection. Traditional deep learning models rely on manual parameter tuning for image segmentation, which limits their efficiency and accuracy. This paper proposes an adaptive Particle Swarm Optimization (PSO) algorithm to optimize the parameters of the U-net model automatically. The algorithm dynamically adjusts the PSO parameters based on the population’s entropy and clustering metrics and employs a hill-climbing algorithm to address the issue of the PSO easily falling into local optima, enhancing the algorithm’s adaptability. The proposed algorithm updates and iterates particles to automatically find suitable model parameters. The remote sensing data used in this experiment were from the Yellow Sea aquaculture area near Dalian, China, with a segmentation accuracy of 91.8%. This method improves segmentation accuracy, reduces the burden of manual parameter tuning, and provides an effective solution for optimizing deep learning models.

关键词： Deep learning Image segmentation Adaptation models Accuracy Heuristic algorithms Clustering algorithms Radar polarimetry Particle swarm optimization Tuning Aquaculture

来源：评论

学校读者我要写书评

暂无评论

Switching control for Identification Deception in Cyber-Physical Systems

Switching Control for Identification Deception in Cyber-Phys...

引用

IEEE Conference on Decision and control

作者： Christos Mavridis Aris Kanellopoulos Henrik Sandberg Karl Henrik Johansson Division of Decision and Control School of Electrical Engineering and Computer Science KTH Royal Institute of Technology Stockholm

ISBN: (数字)9798350316339

ISBN: (纸本)9798350316346

We investigate the problem of deceiving a malicious agent employing an identification method to estimate the closed-loop dynamics of a cyber-physical system. In particular, we propose a moving target defense mechanism that utilizes stochastic switching between linear closed-loop dynamics to drive a linear system identification process of a potential adversary to sub-optimal solutions with non-vanishing error. We provide a statistical analysis of the induced identification error and show that it is not possible for any linear system identification method to reconstruct the average dynamics of a stochastic switched linear system. Finally, we utilize the theory of Markov jump linear systems to guarantee asymptotic stability of the switching system, and formulate the switching control problem as an optimization problem that guarantees stability while taking into account the trade-off between security and switching effort. Simulation results showcase the efficacy of the proposed approach in inducing identification error for the adversary using minimal switching.

关键词： Linear systems Asymptotic stability Switching systems Statistical analysis Simulation Switches Cyber-physical systems control systems Stability analysis Security

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：