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A New Generation of Rules-based Approach:Mivar-based Intelligent Planning of Robot Actions(MIPRA)and Brains for Autonomous Robots

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Machine Intelligence Research 2024年第5期21卷 919-940页

作者： Oleg Varlamov Dmitry Aladin department of information processing and Management Systems RI MIVARBauman Moscow State Tchnical University(BMSTU)Moscow105005Russian Federation

To create autonomous robots,both hardware and software are *** enormous progress has already been made in the field of equipment,then robot software depends on the development of artificial *** article proposes a solution for creating“logical”brains for autonomous robots,namely,an approach for creating an intelligent robot action planner based on Mivar expert *** application of this approach provides opportunities to reduce the computational complexity of solving planning problems and the requirements for the computational characteristics of hardware platforms on which intelligent planning systems are *** theoretically and practically justify the expediency of using logically solving systems,in particular Mivar expert systems,to create intelligent planners,the MIPRA(Mivar-based Intelligent Planning of Robot Actions)planner was created to solve problems such as STRIPS for permutation cubes in the Blocks World *** planner is based on the platform for creating expert systems of the *** a result,the Mivar planner can process information about the state of the subject area based on the analysis of cause-effect relationships and an algorithm for automatically constructing logical inference(finding a solution from“Given”to“Find”).Moreover,an important feature of the MIPRA is that the system is built on the principles of a“white box”,due to which the system can explain any of its decisions and provide justification for the actions performed in the form of a retrospective of the stages of the decision-making *** preparing a set of robot actions aimed at changing control objects,expert knowledge is used,which is the basis for the functioning algorithms of the *** approach makes it possible to include an expert in the process of organizing the work of the intelligent planner and use existing knowledge about the subject *** experiments of this study have shown that instead of many hours and powerfu

关键词： Autonomous robot blocks world decision-making system expert systems intelligent planning

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Detecting Malicious Uniform Resource Locators Using an Applied Intelligence Framework

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Computers, Materials & Continua 2024年第6期79卷 3827-3853页

作者： Simona-Vasilica Oprea Adela Bara department of economic Informatics and Cybernetics Bucharest University of Economic StudiesBucharest010572Romania

The potential of text analytics is revealed by Machine Learning(ML)and Natural Language processing(NLP)*** this paper,we propose an NLP framework that is applied to multiple datasets to detect malicious Uniform Resource Locators(URLs).Three categories of features,both ML and Deep Learning(DL)algorithms and a ranking schema are included in the proposed *** apply frequency and prediction-based embeddings,such as hash vectorizer,Term Frequency-Inverse Dense Frequency(TF-IDF)and predictors,word to vector-word2vec(continuous bag of words,skip-gram)from Google,to extract features from ***,we apply more state-of-the-art methods to create vectorized features,such as ***,feature engineering that is specific to URL structure is deployed to detect scams and other *** framework assessment,four ranking indicators are weighted:computational time and performance as accuracy,F1 score and type error *** the computational time,we propose a new metric-Feature Building Time(FBT)as the cutting-edge feature builders(like doc2vec or GloVe)require more *** applying the proposed assessment step,the skip-gram algorithm of word2vec surpasses other feature builders in ***,eXtreme Gradient Boost(XGB)outperforms other *** this setup,we attain an accuracy of 99.5%and an F1 score of 0.99.

关键词： Detecting malicious URL classifiers text to feature deep learning ranking algorithms feature building time

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Value Iteration-Based Cooperative Adaptive Optimal Control for Multi-Player Differential Games With Incomplete information

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IEEE/CAA Journal of Automatica Sinica 2024年第3期11卷 690-697页

作者： Yun Zhang Lulu Zhang Yunze Cai the department of Automation Shanghai Jiao Tong UniversityShanghai 200240 the Key Laboratory of System Control and information processing Ministry of Education of ChinaShanghai 200240China

This paper presents a novel cooperative value iteration(VI)-based adaptive dynamic programming method for multi-player differential game models with a convergence *** players are divided into two groups in the learning process and adapt their policies *** method removes the dependence of admissible initial policies,which is one of the main drawbacks of the PI-based ***,this algorithm enables the players to adapt their control policies without full knowledge of others’ system parameters or control *** efficacy of our method is illustrated by three examples.

关键词： Adaptive dynamic programming incomplete information multi-player differential game value iteration

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3D Localization for Multiple AUVs in Anchor-Free Environments by Exploring the Use of Depth information

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IEEE/CAA Journal of Automatica Sinica 2024年第4期11卷 1051-1053页

作者： Yichen Li Wenbin Yu Xinping Guan the department of Automation Shanghai Jiao Tong UniversityShanghai 200240 the Key Laboratory of System Control and information processing Ministry of Education of ChinaShanghai Jiao Tong UniversityShanghai 200240China

Dear Editor,This letter investigates the cooperative localization problem for multiple autonomous underwater vehicles(AUVs)in underwater anchor-free environments,where AUV localization errors grow without bound due to the accumulated errors in inertial measurements(termed accumulated errors hereafter)and the lack of anchors(with known positions).

关键词： AUVs underwater hereafter

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Accelerated Primal-Dual Projection Neurodynamic Approach With Time Scaling for Linear and Set Constrained Convex Optimization Problems

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IEEE/CAA Journal of Automatica Sinica 2024年第6期11卷 1485-1498页

作者： You Zhao Xing He Mingliang Zhou Tingwen Huang Chongqing Key Laboratory of Nonlinear Circuits and Intelligent information processing College of Electronic and Information EngineeringSouthwest UniversityChongqing 400715China School of Computer Science Chongqing UniversityChongqing 400044China department of Mathematics Texas A&M University at QatarDoha 23874Qatar IEEE

The Nesterov accelerated dynamical approach serves as an essential tool for addressing convex optimization problems with accelerated convergence *** previous studies in this field have primarily concentrated on unconstrained smooth con-vex optimization *** this paper,on the basis of primal-dual dynamical approach,Nesterov accelerated dynamical approach,projection operator and directional gradient,we present two accelerated primal-dual projection neurodynamic approaches with time scaling to address convex optimization problems with smooth and nonsmooth objective functions subject to linear and set constraints,which consist of a second-order ODE(ordinary differential equation)or differential conclusion system for the primal variables and a first-order ODE for the dual *** satisfying specific conditions for time scaling,we demonstrate that the proposed approaches have a faster conver-gence *** only requires assuming convexity of the objective *** validate the effectiveness of our proposed two accel-erated primal-dual projection neurodynamic approaches through numerical experiments.

关键词： Accelerated projection neurodynamic approach lin-ear and set constraints projection operators smooth and nonsmooth convex optimization time scaling.

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Real-time tracking of fast-moving object in occlusion scene

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Journal of Systems Engineering and Electronics 2024年第3期35卷 741-752页

作者： LI Yuran LI Yichen ZHANG Monan YU Wenbin GUAN Xinping department of Automation Shanghai Jiao Tong UniversityShanghai 200240China Key Laboratory of Systems Control and information processing Ministry of Education of ChinaShanghai 200240China

Tracking the fast-moving object in occlusion situations is an important research topic in computer vision. Despite numerous notable contributions have been made in this field,few of them simultaneously incorporate both object's extrinsic features and intrinsic motion patterns into their methodologies,thereby restricting the potential for tracking accuracy improvement. In this paper, on the basis of efficient convolution operators(ECO) model, a speed-accuracy-balanced model is put forward. This model uses the simple correlation filter to track the object in real-time, and adopts the sophisticated deep-learning neural network to extract high-level features to train a more complex filter correcting the tracking mistakes, when the tracking state is judged to be poor. Furthermore, in the context of scenarios involving regular fast-moving, a motion model based on Kalman filter is designed which greatly promotes the tracking stability, because this motion model could predict the object's future location from its previous movement pattern. Additionally,instead of periodically updating our tracking model and training samples, a constrained condition for updating is proposed,which effectively mitigates contamination to the tracker from the background and undesirable samples avoiding model degradation when occlusion happens. From comprehensive experiments, our tracking model obtains better performance than ECO on object tracking benchmark 2015(OTB100), and improves the area under curve(AUC) by about 8% and 32% compared with ECO, in the scenarios of fast-moving and occlusion on our own collected dataset.

关键词： speed-accuracy balanced motion modeling constrained updater

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Distributed economic MPC for Synergetic Regulation of the Voltage of an Island DC Micro-Grid

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IEEE/CAA Journal of Automatica Sinica 2024年第3期11卷 734-745页

作者： Yi Zheng Yanye Wang Xun Meng Shaoyuan Li Hao Chen IEEE the department of Automation Shanghai Jiao Tong UniversityShanghai 200240 the Key Laboratory of System Control and information processing Ministry of Education of ChinaShanghai 200240China Haixi Institutes Chinese Academy of SciencesJinjiang 362216China

In this paper,distributed model predictive control(DMPC) for island DC micro-grids(MG) with wind/photovoltaic(PV)/battery power is proposed,which coordinates all distributed generations(DG) to stabilize the bus voltage together with the insurance of having computational efficiency under a real-time *** on the feedback of the bus voltage,the deviation of the current is dispatched to each DG according to cost over the prediction ***,to avoid the excessive fluctuation of the battery power,both the discharge-charge switching times and costs are considered in the model predictive control(MPC) optimization problems.A Lyapunov constraint with a time-varying steady-state is designed in each local MPC to guarantee the stabilization of the entire *** voltage stabilization of the MG is achieved by this strategy with the cooperation of *** numeric results of applying the proposed method to a MG of the Shanghai Power Supply Company shows the effectiveness of the distributed economic MPC.

关键词： Distributed model predictive control(DMPC) Lyapunovbased model predictive control micro-grid(MG) voltage control

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A Transformer-Assisted Cascade Learning Network for Choroidal Vessel Segmentation

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Journal of Computer Science & Technology 2024年第2期39卷 286-304页

作者：温阳吴依林毕磊石武祯刘潇骁许毓鹏许迅曹文明冯大淦 Guangdong Provincial Key Laboratory of Intelligent information processing School of Electronics and Information EngineeringShenzhen UniversityShenzhen 518060China Institute of Translational Medicine Shanghai Jiao Tong UniversityShanghai 200240China department of Ophthalmology Shanghai General HospitalShanghai Jiao Tong University School of MedicineShanghai 200080China School of information Technologies The University of SydneySydney 2006Australia

As a highly vascular eye part,the choroid is crucial in various eye disease ***,limited research has focused on the inner structure of the choroid due to the challenges in obtaining sufficient accurate label data,particularly for the choroidal ***,the existing direct choroidal vessel segmentation methods for the intelligent diagnosis of vascular assisted ophthalmic diseases are still unsatisfactory due to noise data,while the synergistic segmentation methods compromise vessel segmentation performance for the choroid layer segmentation *** cascaded structures grapple with error propagation during *** address these challenges,we propose a cascade learning segmentation method for the inner vessel structures of the choroid in this ***,we propose TransformerAssisted Cascade Learning Network(TACLNet)for choroidal vessel segmentation,which comprises a two-stage training strategy:pre-training for choroid layer segmentation and joint training for choroid layer and choroidal vessel *** also enhance the skip connection structures by introducing a multi-scale subtraction connection module designated as MSC,capturing differential and detailed information ***,we implement an auxiliary Transformer branch named ATB to integrate global features into the segmentation *** results exhibit that our method achieves the state-of-the-art performance for choroidal vessel ***,we further validate the significant superiority of the proposed method for retinal fluid segmentation in optical coherence tomography(OCT)scans on a publicly available *** these fully prove that our TACLNet contributes to the advancement of choroidal vessel segmentation and is of great significance for ophthalmic research and clinical application.

关键词： choroidal vessel segmentation optical coherence tomography(OCT) Transformer-assisted cascade learning retinal fluid segmentation multi-scale feature extraction

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A Heuristic Radiomics Feature Selection Method Based on Frequency Iteration and Multi-Supervised Training Mode

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Computers, Materials & Continua 2024年第5期79卷 2277-2293页

作者： Zhigao Zeng Aoting Tang Shengqiu Yi Xinpan Yuan Yanhui Zhu School of Computer Hunan University of TechnologyZhuzhou412007China Hunan Key Laboratory of Intelligent information Perception and processing Technology Zhuzhou412007China

Radiomics is a non-invasive method for extracting quantitative and higher-dimensional features from medical images for *** has received great attention due to its huge application prospects in recent *** can know that the number of features selected by the existing radiomics feature selectionmethods is basically about *** this paper,a heuristic feature selection method based on frequency iteration and multiple supervised training mode is *** on the combination between features,it decomposes all features layer by layer to select the optimal features for each layer,then fuses the optimal features to form a local optimal group layer by layer and iterates to the global optimal combination *** with the currentmethod with the best prediction performance in the three data sets,thismethod proposed in this paper can reduce the number of features fromabout ten to about three without losing classification accuracy and even significantly improving classification *** proposed method has better interpretability and generalization ability,which gives it great potential in the feature selection of radiomics.

关键词： Radiomics feature selection machine learning metaheuristic

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RoBGP:A Chinese Nested Biomedical Named Entity Recognition Model Based on RoBERTa and Global Pointer

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Computers, Materials & Continua 2024年第3期78卷 3603-3618页

作者： Xiaohui Cui Chao Song Dongmei Li Xiaolong Qu Jiao Long Yu Yang Hanchao Zhang School of information Science and Technology Beijing Forestry UniversityBeijing100083China Engineering Research Center for Forestry-Oriented Intelligent information processing of National Forestry and Grassland Administration Beijing100083China Division of Biostatistics Department of Population HealthGrossman School of MedicineNew York UniversityNew York10016USA

Named Entity Recognition(NER)stands as a fundamental task within the field of biomedical text mining,aiming to extract specific types of entities such as genes,proteins,and diseases from complex biomedical texts and categorize them into predefined entity *** process can provide basic support for the automatic construction of knowledge *** contrast to general texts,biomedical texts frequently contain numerous nested entities and local dependencies among these entities,presenting significant challenges to prevailing NER *** address these issues,we propose a novel Chinese nested biomedical NER model based on RoBERTa and Global Pointer(RoBGP).Our model initially utilizes the RoBERTa-wwm-ext-large pretrained language model to dynamically generate word-level initial *** then incorporates a Bidirectional Long Short-Term Memory network for capturing bidirectional semantic information,effectively addressing the issue of long-distance ***,the Global Pointer model is employed to comprehensively recognize all nested entities in the *** conduct extensive experiments on the Chinese medical dataset CMeEE and the results demonstrate the superior performance of RoBGP over several baseline *** research confirms the effectiveness of RoBGP in Chinese biomedical NER,providing reliable technical support for biomedical information extraction and knowledge base construction.

关键词： Biomedicine knowledge base named entity recognition pretrained language model global pointer

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