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Tracking Control in Presence of Obstacles and Uncertainties for Bioinspired Spherical Underwater Robots

Journal of Bionic engineering 2023年第1期20卷 323-337页

作者： Chunying Li Shuxiang Guo Jian Guo Graduate School of Engineering Kagawa UniversityTakamatsuKagawa761-0396Japan Key Laboratory of Convergence Medical Engineering System and Healthcare Technology the Ministry of Industry and Information TechnologySchool of Life Science and TechnologyBeijing Institute of TechnologyBeijing100081China Tianjin Key Laboratory for Control Theory and Applications in Complicated Systems and Intelligent Robot Laboratory Tianjin University of TechnologyBinshui Xidao Extension 391Tianjin300384China

During marine missions,AUVs are susceptible to external disturbances,such as obstacles,ocean currents,etc.,which can easily cause mission failure or *** this paper,considering the strong nonlinearities,external disturbances and obstacles,the kinematic and dynamic model of bioinspired Spherical Underwater Robot(SUR)was ***,the waypoints-based trajectory tracking with obstacles and uncertainties was proposed for SUR to guarantee its safety and ***,the Lyapunov theory was adopted to verify the stability and the Slide Mode Control(SMC)method is used to verify the robustness of the control *** addition,a series of simulations were conducted to evaluate the effectiveness of proposed control *** tests,including path-following,static and moving obstacle avoidance were performed which verified the feasibility,robustness and effectiveness of the designed control ***,a series of experiments in real environment were performed to verify the performance of the control *** simulation and experimental results of the study supplied clues to the improvement of the path following capability and multi-obstacle avoidance of AUVs.

关键词： Path following Obstacle avoidance Bioinspired.Spherical underwater robot(SUR) Lyapunov theory

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Review of data security within energy blockchain:A comprehensive analysis of storage,management,and utilization

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High-Confidence Computing 2024年第3期4卷 82-102页

作者： Yunhua He Zhihao Zhou Yan Pan Fahui Chong Bin Wu Ke Xiao Hong Li School of Information Science and Technology North China University of TechnologyBeijing 100144China China Industrial Control Systems Cyber Emergency Response Team Beijing 100040China Key Laboratory in Blockchain and Data Security by Ministry of Industry and Information Technology Beijing 100040China Institute of Information Engineering Chinese Academy of Sciences Beijing 100195China

Energy systems are currently undergoing a transformation towards new paradigms characterized by decarbonization,decentralization,democratization,and *** this evolving context,energy blockchain,aiming to enhance efficiency,transparency,and security,emerges as an integrated technological solution designed to address the diverse challenges in this *** security is essential for the reliable and efficient functioning of energy *** pressing need to address challenges related to secure data storage,effective data management,and efficient data utilization is increasingly *** paper offers a comprehensive survey of academic discourse on energy blockchain data security over the past five years,adopting an all-encompassing perspective that spans data storage,management,and *** work systematically evaluates and contrasts the strengths and weaknesses of various research ***,this paper proposes an integrated hierarchical on-chain and off-chain security energy blockchain architecture,specifically designed to meet the complex security requirements of multi-blockchain business ***,this paper identifies key directions for future research,particularly in advancing the integration of storage,management,and utilization of energy blockchain data security.

关键词： Energy blockchain Data security Storage Management Utilization

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Safe motion planning and formation control of quadruped robots

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Autonomous Intelligent systems 2024年第1期4卷 38-49页

作者： Zongrui Ji Yi Dong College of Electronic and Information Engineering National Key Laboratory of Autonomous Intelligent Unmanned SystemsFrontiers Science Center for Intelligent Autonomous SystemsMinistry of EducationTongji UniversityShanghai 200092China

This paper introduces a motion planning and cooperative formation control approach for quadruped robots and multi-agent ***,in order to improve the efficiency and safety of quadruped robots navigating in complex environments,this paper proposes a new planning method that combines the dynamic model of quadruped robots and a gradient-optimized obstacle avoidance strategy without Euclidean Signed Distance *** framework is suitable for both static and slow dynamic obstacle environments,aiming to achieve multiple goals of obstacle avoidance,minimizing energy consumption,reducing impact,satisfying dynamic constraints,and ensuring trajectory *** approach differs in that it reduces energy consumption throughout the movement from a new ***,this method effectively reduces the impact of the ground on the robot,thus mitigating the damage to its ***,we combine the dynamic control barrier function and the virtual leader-follower model to achieve efficient and safe formation control through model predictive ***,the proposed algorithm is validated through both simulations and real-world scenarios testing.

关键词： Efficient motion planning Dynamic model Safety-critical Model predictive control

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Matching Knowledge Graphs in Entity Embedding Spaces: An Experimental Study [Extended Abstract] 40

Matching Knowledge Graphs in Entity Embedding Spaces: An Exp...

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40th IEEE International Conference on Data engineering, ICDE 2024

作者： Zeng, Weixin Zhao, Xiang Tan, Zhen Tang, Jiuyang Cheng, Xueqi National University of Defense Technology Laboratory for Big Data and Decision China National University of Defense Technology Science and Technology on Information Systems Engineering Laboratory China Institute of Computing Technology CAS China

ISBN: (纸本)9798350317152

Entity alignment (EA) identifies equivalent entities that locate in different knowledge graphs (KGs), and has attracted growing research interests over the last few years with the advancement of KG embedding techniques. Although a pile of embedding-based EA frameworks have been developed, they mainly focus on improving the performance of entity representation learning, while largely overlook the subsequent stage that matches KGs in entity embedding spaces. Nevertheless, accurately matching entities based on learned entity representations is crucial to the overall alignment performance, as it coordinates individual alignment decisions and determines the global matching result. Hence, it is essential to understand how well existing solutions for matching KGs in entity embedding spaces perform on present benchmarks, as well as their strengths and weaknesses. To this end, in this article we provide a comprehensive survey and evaluation of matching algorithms for KGs in entity embedding spaces in terms of effectiveness and efficiency on both classic settings and new scenarios that better mirror real-life challenges. Based on in-depth analysis, we provide useful insights into the design trade-offs and good paradigms of existing works, and suggest promising directions for future development. © 2024 IEEE.

关键词： Embeddings

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Design of a Hybrid AI- based Phishing Website Detection using LSTM, CNN, and Random Forest based Ensemble Learning Analysis 8

Design of a Hybrid AI- based Phishing Website Detection usin...

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8th International Conference on Electronics, Communication and Aerospace technology, ICECA 2024

作者： Kavya, S. Sumathi, D. Vellore Institute of Technology School of Computer Science Engineering and Information Systems Vellore India

ISBN: (纸本)9798350367904

Phishing attacks are always surfacing as key threats against internet users, necessitating advanced detection methods. Blacklist-based systems and rule-based models of phishing detection generally have had critical limitations in dealing with evolving tactics and new phishing schemes. Some of these approaches fail to cope with the temporal and visual patterns of phishing sites, which are crucial for timely and accurate detection. To overcome these difficulties, this work introduces a hybrid AI-based phishing website detection model that utilizes several machine learning and deep learning techniques to improve the accuracy of the detection and remove false positives. The proposed model uses LSTM networks, Genetic Algorithms, Random Forest, and CNN through the stacking ensemble framework. Since LSTM is adopted to capture the temporal dependencies in the website traffic and user interaction patterns, this model can effectively model their phishing behavior over time. GA is used for bioinspired feature selection to reduce the dimensionality of features while optimizing model performance. Random Forest is used as a base layer addressing structured features like URL characteristics and WHOIS information. CNNs are incorporated to extract feature content from a webpage and images that carry various visual indicators often used in phishing attacks including counterfeit logos or banners. A meta-classifier is then used to combine the outputs of LSTMs, CNN, and RF and generate the final classification to boost the detection rate. The proposed hybrid model surpasses the existing techniques and facilitates the analysis of temporal, visual, and structured data, making the detection considerably more accurate. Achieving accuracy of as much as 96-97% and having an AUC of 0.97 with a false positive rate below 3%, the model then impacts the more powerful and more flexible phishing detection system, which is then capable of being more protective against higher sophisticated phishing te

关键词： Phishing

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CropViT: A light-weight Transformer Model for Crop Disease Detection 3

CropViT: A light-weight Transformer Model for Crop Disease D...

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3rd International Conference on Artificial Intelligence For Internet of Things, AIIoT 2024

作者： Chemmalar Selvi, G. Charan, H.J. Kumar, Dinesh Vellore Institute of Technology School of Computer Science Engineering and Information Systems Vellore India

ISBN: (纸本)9798350372120

Agricultural industry has grown significantly bring sustainable farming practices in improving the food quality, enhancing agricultural productivity and global food security. However, the crop yield and its quality are impacted when the timely identification and management of the crop diseases are not promptly solved. Thus, the crop disease detection becomes the critical aspect in the smart agriculture. Several researchers addressed this crop disease detection by developing optimized solutions through machine learning, deep learning and image processing techniques. However, these techniques face serious challenges when deployed in real-time crop disease identification problems like annotated training images, capturing long-range dependencies, adaption to real-time changes evolving over time and so on. This leads to performance degradation seeking for more powerful applications like some advanced deep learning techniques, in particular, the transformer models. In this paper, a novel crop disease detection model known as CropViT was proposed based on Vision Transformer. This CropViT was developed by fine-tuning the architecture of existing Vision Transformer and PlantVillage dataset was used in the experimental study. Nine crop species were selected and trained using CropViT whose performance was then compared with traditional Convolutional Neural Network model. The experimental study clearly showed the highest mean accuracy of 98.64% for CropViT when compared to 95.52% mean accuracy for traditional CNN. The experimental results also outperformed other existing state-of-the-art models. Finally, the work was concluded with the discussion of experimental results and its future scope of work. © 2024 IEEE.

关键词： Convolutional neural networks

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Heteronuclear Magnetisms with Ultracold Spinor Bosonic Gases in Optical Lattices

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Chinese Physics Letters 2024年第2期41卷 69-82页

作者： Yongqiang Li Chengkun Xing Ming Gong Guangcan Guo Jianmin Yuan Department of Physics National University of Defense TechnologyChangsha 410073China Hunan Key Laboratory of Extreme Matter and Applications National University of Defense TechnologyChangsha 410073China Key Lab of Quantum Information(CAS) University of Science and Technology of ChinaHefei 230026China CAS Key Laboratory of Quantum Information University of Science and Technology of ChinaHefei 230026China Synergetic Innovation Center of Quantum Information and Quantum Physics University of Science and Technology of ChinaHefei 230026China Hefei National Laboratory University of Science and Technology of ChinaHefei 230088China Department of Physics Graduate School of China Academy of Engineering PhysicsBeijing 100193China

Motivated by recent realizations of spin-1 NaRb mixtures in the experiments[***.114,255301(2015);***.128,223201(2022)],we investigate heteronuclear magnetism in the Mott-insulating *** from the identical mixtures where the boson statistics only admits even parity states from angular momentum composition,for heteronuclear atoms in principle all angular momentum states are allowed,which can give rise to new magnetic *** various magnetic phases can be developed over these degenerate spaces,the concrete symmetry breaking phases depend on not only the degree of degeneracy but also the competitions from many-body *** unveil these rich phases using the bosonic dynamical mean-field theory *** phases are characterized by various orders,including spontaneous magnetization order,spin magnitude order,singlet pairing order,and nematic order,which may coexist specially in the regime with odd *** we address the possible parameter regimes for observing these spin-ordered Mott phases.

关键词： parity momentum allowed

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Sequence structure controllable polymerization-induced self-assembly

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science China Chemistry 2024年第1期67卷 390-397页

作者： Zi-Xuan Chang Ren-Man Zhu Chun-Yan Hong Wen-Jian Zhang Department of Polymer Science and Engineering University of Science and Technology of ChinaHefei 230026China Institute of Physical Science and Information Technology Anhui UniversityHefei 230601China Key Laboratory of Environment-Friendly Polymeric Materials of Anhui Province Anhui UniversityHefei 230601China

Polymerization-induced self-assembly(PISA)combines synthesis and self-assembly of artificial polymers in one-pot,which brings us one step closer to emulating ***,the reported PISA formulations primarily focus on developing nano-objects with new chemical compositions and rarely on structural regulation of polymers with specific ***,sequence structure controllable polymerization-induced self-assembly(SCPISA)is reported by using 7-(2-methacryloyloxyethoxy)-4-methylcoumarin(CMA)as a *** the copolymerization of 2-hydroxyethyl methacrylate(HEMA)and CMA,controlled incorporation of CMA units into the polymer chains can be realized by programmable light/heat ***-based P(HEMA-co-CMA)copolymers with the same composition but different sequence structures generate a range of ***,the morphologies of the resultant nano-objects can also be controlled by regulating the feed molar ratio of CMA and HEMA,which is similar to the conventional PISA,but the synthesis procedure is obviously simplified in *** versatility of the methodology is further demonstrated by the fabrication of different functional nano-objects with sequence structure-dependent morphologies in SCPISA systems with different functional monomers.

关键词： polymerization-induced self-assembly sequence-controlled polymers PET-RAFT polymerization

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Boosting bulk photovoltaic effect in transition metal dichalcogenide by edge semimetal contact

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Light(science & Applications) 2025年第1期14卷 197-205页

作者： Shuang Qiao Jihong Liu Chengdong Yao Ni Yang Fangyuan Zheng Wanqing Meng Yi Wan Philip C.Y.Chow Dong-Keun Ki Lijie Zhang Yumeng Shi Lain-Jong Li Hebei Key Laboratory of Optic-Electronic Information and Materials College of Physics Science and TechnologyHebei University071002BaodingChina Department of Mechanical Engineering The University of Hong KongHong KongChina Department of Physics and HK Institute of Quantum Science&Technology The University of Hong KongHong KongChina Key Laboratory of Carbon Materials of Zhejiang Province College of Chemistry and Materials EngineeringWenzhou UniversityWenzhouChina Key Laboratory of Luminescence and Optical Information Ministry of EducationSchool of Physical Science and EngineeringBeijing Jiaotong University100044BeijingChina

Oxide materials with a non-centrosymmetric structure exhibit bulk photovoltaic effect(BPVE)but with a low cell *** the past few years,relatively larger BPVE coefficients have been reported for two-dimensional(2D)layers and stacks with asymmety-induced spontaneous ***,we report a crucial breakthrough in boosting the BPVE in 3R-MoS2 by adopting edge contact(EC)geometry using bismuth semimetal *** clear contrast to the typically used top contact(TC)geometry,the EC metal which strongly adheres to the edges and the subtrates can induce a pronounced tensile strain to the 3R-MoS2,and the lateral contact geometry allows to completely access to in-plane polarization from underneath layers reachable by light,leading to>100 times of BPVE enhancement in *** further design a 3R-MoS2/WSe2 heterojunction to demonstrate constructive coupling of BPVE with the conventional photovoltaic effect,indicating their potential in photodetectors and photovoltaic devices.

关键词： effect geometry breakthrough

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Enhanced Road Safety Through Intelligent Lane Detection and Driver Drowsiness Monitoring 15

Enhanced Road Safety Through Intelligent Lane Detection and ...

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15th International Conference on Computing Communication and Networking Technologies, ICCCNT 2024

作者： Arunpandian, J. Gunasekaran, V. Vellore Institute of Technology School of Computer Science Engineering and Information Systems Vellore India

ISBN: (纸本)9798350370249

The innovative system outlined in the provided research demonstrates a significant stride towards addressing the growing concern of road safety. Lane departure and driver drowsiness are two major causes of road accidents. In this paper, we present an observation of road lane and drowsiness detection system that uses a camera to capture real-time video footage of the road ahead and applies image processing techniques to detect and track road lanes. The system's road lane detection module employs the canny edge detection algorithm and Hough transform to detect lane lines accurately. The drowsiness detection module of the system analyzes the driver's facial features and tracks the driver's eye movements, blink frequency to identify signs of drowsiness. If the driver found to be sleepy, it issues an audio alert to the driver. The system's capability to detect and track road lanes with precision, along with its ability to identify signs of driver drowsiness, underscores its potential as a promising solution for enhancing road safety. © 2024 IEEE.

关键词： Canny edge algorithm drowsiness lane detection road safety vehicles

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