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Fully implantable wireless brain-computer interface for humans: Advancing toward the future

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The Innovation 2024年第3期5卷 3-4页

作者： Zhiting Zhang Ji Dai Shenzhen Technological Research Center for Primate Translational Medicine Shenzhen-Hong Kong Institute of Brain ScienceShenzhen Institute of Advanced TechnologyChinese Academy of SciencesShenzhen 518055China CAS Key Laboratory of Brain Connectome and Manipulation the Brain Cognition and Brain Disease InstituteShenzhen Institute of Advanced TechnologyChinese Academy of SciencesShenzhen 518055China Guangdong Provincial Key Laboratory of Brain Connectome and Behavior Shenzhen Institute of Advanced TechnologyChinese Academy of SciencesShenzhen 518055China University of Chinese Academy of Sciences Beijing 100049China

On January 29,2024,Elon Musk made a public announcement via social media about the successful implantation of a Neuralink device in humans.Shortly after,a collaborative team from Xuanwu Hospital and Tsinghua University in China revealed the advancements in their clinical experiment testing the Neural Electronic Opportunity(NEO)—a wireless brain-computer interface(BCI).1 These simultaneous developments sparked widespread interest and renewed enthusiasm for BCIs worldwide.

关键词： wireless computer interface

A framework of force of information influence and application for C4KISR system

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Journal of Systems Engineering and Electronics 2024年第2期35卷 430-443页

作者： MAO Shaojie DIAO Lianwang SUN Yu WANG Heng YI Kan XU Xin MAO Xiaobin ZHANG Kecheng SHENG Long Science and Technology on Information Systems Engineering Laboratory The 28th Research Institute of China Electronics Technology Group CorporationNanjing 210007China Unit 94860 of the PLA Nanjing 210008China

The subversive nature of information war lies not only in the information itself, but also in the circulation and application of information. It has always been a challenge to quantitatively analyze the function and effect of information flow through command, control, communications, computer, kill, intelligence,surveillance, reconnaissance (C4KISR) system. In this work, we propose a framework of force of information influence and the methods for calculating the force of information influence between C4KISR nodes of sensing, intelligence processing,decision making and fire attack. Specifically, the basic concept of force of information influence between nodes in C4KISR system is formally proposed and its mathematical definition is provided. Then, based on the information entropy theory, the model of force of information influence between C4KISR system nodes is constructed. Finally, the simulation experiments have been performed under an air defense and attack scenario. The experimental results show that, with the proposed force of information influence framework, we can effectively evaluate the contribution of information circulation through different C4KISR system nodes to the corresponding tasks. Our framework of force of information influence can also serve as an effective tool for the design and dynamic reconfiguration of C4KISR system architecture.

关键词： information warfare command control communications computer kill intelligence surveillance reconnaissance(C4KISR)system information circulation force of information influence information entropy

Evolutionary Optimization Methods for High-Dimensional Expensive Problems:A Survey

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IEEE/CAA Journal of Automatica Sinica 2024年第5期11卷 1092-1105页

作者： MengChu Zhou Meiji Cui Dian Xu Shuwei Zhu Ziyan Zhao Abdullah Abusorrah Department of Electrical and computer Engineering New Jersey Institute of TechnologyNewarkNJ 07102 USA School of Information and Electronic Engineering Zhejiang Gongshang UniversityHangzhou 310018China School of Intelligent Manufacturing Nanjing University of Science and TechnologyNanjing 210094China Institute of Systems Engineering Macao University of Science and TechnologyMacao 999078China School of Artificial Intelligence and computer Jiangnan UniversityWuxi 214122China School of Information Science and Engineering Northeastern UniversityShenyang 110819China Center of Research Excellence in Renewable Energy and Power Systems Department of Electrical and Computer EngineeringFaculty of EngineeringKing Abdulaziz UniversityJeddah 21589Saudi Arabia K.A.CARE Energy Research and Innovation Center King Abdulaziz UniversityJeddah 21589Saudi Arabia

Evolutionary computation is a rapidly evolving field and the related algorithms have been successfully used to solve various real-world optimization problems.The past decade has also witnessed their fast progress to solve a class of challenging optimization problems called high-dimensional expensive problems(HEPs).The evaluation of their objective fitness requires expensive resource due to their use of time-consuming physical experiments or computer simulations.Moreover,it is hard to traverse the huge search space within reasonable resource as problem dimension increases.Traditional evolutionary algorithms(EAs)tend to fail to solve HEPs competently because they need to conduct many such expensive evaluations before achieving satisfactory results.To reduce such evaluations,many novel surrogate-assisted algorithms emerge to cope with HEPs in recent years.Yet there lacks a thorough review of the state of the art in this specific and important area.This paper provides a comprehensive survey of these evolutionary algorithms for HEPs.We start with a brief introduction to the research status and the basic concepts of HEPs.Then,we present surrogate-assisted evolutionary algorithms for HEPs from four main aspects.We also give comparative results of some representative algorithms and application examples.Finally,we indicate open challenges and several promising directions to advance the progress in evolutionary optimization algorithms for HEPs.

关键词： computer optimization evolutionary

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Object Helps U-Net Based Change Detectors

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IEEE/CAA Journal of Automatica Sinica 2024年第2期11卷 548-550页

作者： Lan Yan Qiang Li Kenli Li College of computer Science and Electronic Engineering Hunan UniversityChangsha 410082China State Key Laboratory for Management and Control of Complex Systems Institute of AutomationChinese Academy of SciencesBeijing 100190China

Dear Editor,This letter focuses on leveraging the object information in images to improve the performance of the U-Net based change detector.Change detection is fundamental to many computer vision tasks.Although exist... 详细信息

关键词： Net computer networks

Parallel Vision ■ Image Synthesis/Augmentation

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IEEE/CAA Journal of Automatica Sinica 2024年第3期11卷 782-784页

作者： Wenwen Zhang Wenbo Zheng Qiang Li Fei-Yue Wang the School of computer Science Shaanxi Normal UniversityXi’an 710119China the School of computer Science and Technology Wuhan 430070China the State Key Laboratory for Management and Control of Complex Systems Institute of AutomationChinese Academy of SciencesBeijing 100190China

Dear Editor,Scene understanding is an essential task in computer vision.The ultimate objective of scene understanding is to instruct computers to understand and reason about the scenes as humans do.Parallel vision is ... 详细信息

关键词： instru explanation computer

Parallel Light Fields: A Perspective and A Framework

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IEEE/CAA Journal of Automatica Sinica 2024年第2期11卷 542-544页

作者： Fei-Yue Wang Yu Shen IEEE State Key Laboratory for Management and Control of Complex Systems Institute of AutomationChinese Academy of SciencesBeijing 100190China School of Artificial Intelligence University of Chinese Academy of ScienceBeijing 100049

Dear Editor,Light fields give relatively complete description of scenes from perspective of angles and positions of rays. At present time, most of the computer vision algorithms take 2D images as input which are simplified expression of light fields with depth information discarded. In theory, computer vision tasks may achieve better performance as long as complete light fields are acquired.

关键词： computer Framework simplified

Two-Way Neural Network Performance PredictionModel Based onKnowledge Evolution and Individual Similarity

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computer Modeling in Engineering & Sciences 2024年第2期138卷 1183-1206页

作者： Xinzheng Wang Bing Guo Yan Shen College of computer Science Sichuan UniversityChengdu610065China School of Information Science and Engineering Guilin University of TechnologyGuilin541004China School of Control Engineering Chengdu University of Information TechnologyChengdu610225China

Predicting students’academic achievements is an essential issue in education,which can benefit many stakeholders,for instance,students,teachers,managers,etc.Compared with online courses such asMOOCs,students’academicrelateddata in the face-to-face physical teaching environment is usually sparsity,and the sample size is relativelysmall.It makes building models to predict students’performance accurately in such an environment even morechallenging.This paper proposes a Two-WayNeuralNetwork(TWNN)model based on the bidirectional recurrentneural network and graph neural network to predict students’next semester’s course performance using only theirprevious course achievements.Extensive experiments on a real dataset show that our model performs better thanthe baselines in many indicators.

关键词： computer education performance prediction deep learning

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激光诱导石墨烯实现可拉伸的多模态传感

Science Bulletin 2024年第11期69卷 1601-1603页

作者：李杨顾雨哲庞芸聪赵强 College of Electronic and Optical Engineering&College of Flexible Electronics(Future Technology) Nanjing University of Posts&Telecommunications(NJUPT)Nanjing 210023China State Key Laboratory of Organic Electronics and Information Displays&Jiangsu Key Laboratory for Biosensors Institute of Advanced Materials(IAM)Nanjing University of Posts&Telecommunications(NJUPT)Nanjing 210023China

Multimodal sensing, achieved by integrating multiple sensors on a flexible substrate, whether worn or implanted, facilitates versatile and highly sensitive monitoring of diverse signals(physical,chemical, electrophysiological), aiding in device miniaturization and finding extensive applications in human–machine interaction,health monitoring, brain–computer interfaces, disease management, and drug delivery [1].

关键词： computer 激光诱导多模态

Application and prospects of computer-assisted surgery in oral and maxillofacial oncology

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Science Bulletin 2023年第3期68卷 236-239页

作者： Xin Peng Julio Acero Guang-Yan Yu Department of Oral and Maxillofacial Surgery Peking University School and Hospital of StomatologyNational Clinical Research Center for Oral DiseasesNational Engineering Laboratory for Digital and Material Technology of StomatologyBeijing Key Laboratory of Digital StomatologyBeijing 100081China Department of Oral and Maxillofacial Surgery Ramón y Cajal and Puerta de Hierro University HospitalsUniversity of AlcalaRamón y Cajal Research Institute(IRYCIS)Madrid 28034Spain

The primary treatment modality for tumors affecting the oral and maxillofacial region is surgery.Surgical treatment of tumors affecting this region is a challenge and poses relatively high surgical risk,especially in lesions affecting the deep regions of the head and the neck due to the complex anatomy of this region including structures of great importance such as the internal carotid artery,the internal jugular vein,and the cavernous sinus at the skull base,the cranial nerves and the orbital contents with the eye globes,extraocular muscles,and the lacrimal gland.Oncologic resection often results in devastating defects in the oral and maxillofacial region,which adversely affect patients’facial appearance and important functions such as speech,chewing,deglutition,or vision and significantly impact patients’quality of life.In order to obtain a good result concerning tumor excision in the oral and cranio-maxillofacial region as well as a correct aesthetic and functional reconstruction,an adequate presurgical evaluation of the patient and accurate planning of the surgical resection and the reconstructive approach must be carefully designed.

关键词： surgery anatomy computer