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Sora for foundation robots with parallel intelligence:three world models,three robotic systems

Frontiers of information Technology & Electronic Engineering 2024年第7期25卷 917-923页

作者： Lili FAN Chao GUO Yonglin TIAN Hui ZHANG Jun ZHANG Fei-Yue WANG School of Information and Electronics Beijing Institute of TechnologyBeijing 100081China State Key Laboratory for Management and Control of Complex Systems Institute of AutomationChinese Academy of SciencesBeijing 100190China School of Computer and Information Technology Beijing Jiaotong UniversityBeijing 100044China School of Electrical Engineering Wuhan UniversityWuhan 430072China

This paper outlines the initial steps and basic framework for developing foundation/infrastructure robots/robotics based on foundation models and parallel intelligence,as well as the potential applications of new art... 详细信息

关键词： artificial foundation intelligence

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Proposal and Evaluation of Adaptive Multimedia Utilization Method for Reliable Web Based Collaboration

Proposal and Evaluation of Adaptive Multimedia Utilization M...

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International IEEE Conference on Signal-Image Technologies and Internet-Based System

作者： Yoshitaka Sakurai Kinshuk Sabine Graf Ardah Zarypolla Kouhei Takada Rainer Knauf Setsuo Tsuruta School of Information Environment Tokyo Denki University Japan School of Computing and Information Systems Athabasca University Canada Faculty of Computer Science and Automation University of Ilmenau Ilmenau Germany

Due to the geographical distribution, different cognitive capacity, and different domain competency of workers or learners, many misunderstandings can occur during Web based remote collaboration, leading to inefficient discussions and undesired results. To overcome these problems, a “Multimedia adaptive utilization” framework for dependable web based collaboration is proposed and evaluated. This assesses situations of remote users through fusing information of multiple biological sensors and the related contexts such as user profiles. Transmitting and using such information, the system adaptively supports Web based remote collaboration by stressing, warning, and presenting keywords/ summaries in multimedia. Then, effects of adaptive keyword/summary presentation are evaluated as to cognitive profiles of users such as short term memory capacity and associative learning skills when misunderstanding possibilities are estimated on the Web. These evaluations totally demonstrate the feasibility and usefulness of the proposed method.

关键词： Collaboration Biosensors Microphones Skin Avatars Multimedia communication Cyberspace

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Enriched Cyberspace through Adaptive Multimedia Utilization for Dependable Remote Collaboration

Enriched Cyberspace through Adaptive Multimedia Utilization ...

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International Conference on Advanced information Networking and Applications Workshops (AINAW)

作者： Yoshitaka Sakurai Kinshuk Kouhei Takada Rainer Knauf Setsuo Tsuruta School of Information Environment Tokyo Denki University Japan School of Computing and Information Systems Athabasca University Canada Faculty of Computer Science and Automation University of Ilmenau Ilmenau Germany

Due to the geographical distribution, different cognitive capacity, and different domain competency of workers or learners, many misunderstandings can occur during distributed remote collaboration, leading to inefficient discussions and undesired results. To make remote collaboration more efficient and dependable, enriching cyberspace through adaptively utilizing is proposed and evaluated. This assesses situations of remote users through information fusion of multiple biological sensors and the related contexts such as user profiles. Transmitting and using such information, the system adaptively supports the distributed remote collaboration by stressing, warning, and presenting keywords/summaries in multimedia. Effects of presenting keywords/summaries adaptively depending on situations and cognitive profiles of remote members are evaluated as to the decrease of not-/misunderstanding possibilities during the explanation on the Cyberspace. The evaluation demonstrates the feasibility and usefulness of the proposed method.

关键词： Collaborative work Collaborative tools Multimedia systems International collaboration Guidelines Humans Application software Conferences Multimedia computing computer networks

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Associative learning mechanism for drug‐target interaction prediction

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CAAI Transactions on Intelligence Technology 2023年第4期8卷 1558-1577页

作者： Zhiqin Zhu Zheng Yao Guanqiu Qi Neal Mazur Pan Yang Baisen Cong College of Automation Chongqing University of Posts and TelecommunicationsChongqingChina Computer Information Systems Department State University of New York at Buffalo StateBuffaloNew YorkUSA Department of Cardiovascular Surgery Chongqing General HospitalUniversity of Chinese Academy of SciencesChongqingChina Emergency Department The Second Affiliated Hospital of Chongqing Medical UniversityChongqingChina Data Scientist Diagnostics Digital DH(Shanghai)Diagnostics Co.Ltd.Danaher CompanyShanghaiChina

As a necessary process of modern drug development,finding a drug compound that can selectively bind to a specific protein is highly challenging and *** drug‐target interaction strength in terms of drug‐target affinity(DTA)is an emerging and effective research approach for drug ***,it is challenging to model drug‐target interactions in a deep learning manner,and few studies provide interpretable analysis of *** paper proposes a DTA prediction method(mutual transformer‐drug target affinity[MT‐DTA])with interactive learning and an autoencoder *** proposed MT‐DTA builds a variational autoencoders system with a cascade structure of the attention model and convolutional neural *** not only enhances the ability to capture the characteristic information of a single molecular sequence but also establishes the characteristic expression relationship for each substructure in a single molecular *** this basis,a molecular information interaction module is constructed,which adds information interaction paths between molecular sequence pairs and complements the expression of correlations between molecular *** performance of the proposed model was verified on two public benchmark datasets,KIBA and Davis,and the results confirm that the proposed model structure is effective in predicting ***,attention transformer models with different configurations can improve the feature expression of drug/protein *** model performs better in correctly predicting interaction strengths compared with state‐of‐the‐art *** addition,the diversity of drug/protein molecules can be better expressed than existing methods such as SeqGAN and Co‐VAE to generate more effective new *** DTA value prediction module fuses the drug‐target pair interaction information to output the predicted value of ***,this paper theoretically proves that the proposed method maximises evidence lower bound

关键词： deep learning medical applications

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Evaluation of Enriched Cyberspace for Adaptive Support of Remote Collaboration

Evaluation of Enriched Cyberspace for Adaptive Support of Re...

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International IEEE Conference on Signal-Image Technologies and Internet-Based System

作者： Yoshitaka Sakurai Kinshuk Kouhei Takada Takashi Kawabe Rainer Knauf Setsuo Tsuruta School of Information Environment Tokyo Denki University Japan School of Computing and Information Systems Athabasca University Canada Faculty of Computer Science and Automation University of Ilmenau Ilmenau Germany

Due to the geographical distribution, different cognitive capacity, and different domain competency of workers or learners, many misunderstandings can occur during distributed remote collaboration, leading to inefficient discussions and undesired results. To make remote collaboration more efficient and dependable, enriching cyberspace through adaptively utilizing is proposed and evaluated. This assesses situations of remote users through information fusion of multiple biological sensors and the related contexts such as user profiles. Transmitting and using such information, the system adaptively supports the distributed remote collaboration by stressing, warning, and presenting keywords/summaries in multimedia. Effects of presenting keywords/summaries adaptively depending on situations are evaluated as to the decrease of not-/misunderstanding possibilities during the explanation on the Cyberspace. Moreover, the adaptive selection effects of keywords or summaries presentation depending on cognitive profiles of remote members are also evaluated. These evaluations demonstrate the feasibility and usefulness of the proposed method.

关键词： Collaboration Cyberspace Biosensors Microphones Temperature sensors Skin Avatars

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Classification with the hybrid of manifold learning and gabor wavelet

Classification with the hybrid of manifold learning and gabo...

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3rd International Symposium on Neural Networks, ISNN 2006 - Advances in Neural Networks

作者： Zhang, Junping Shen, Chao Feng, Jufu Shanghai Key Laboratory of Intelligent Information Processing Department of Computer Science and Engineering Fudan University Shanghai 200433 China Key Laboratory of Complex Systems and Intelligence Science Institute of Automation Chinese Academy of Sciences Beijing 100080 China National Key Laboratory for Machine Perception School of Electronics Engineering and Computer Science Peking University Beijing 100871 China

ISBN: (纸本)354034439X

While manifold learning algorithms can discover intrinsic low-dimensional manifold embedded in the high-dimensional Euclidean space, the discriminant ability of the low-dimensional subspaces obtained by the algorithms is often lower than those obtained by the conventional dimensionality reduction approaches. Furthermore, the original feature vectors may include redundancy such as high-order correlation which cannot be removed by manifold learning algorithms. To address the two problems, we first employ Gabor wavelet to remove intrinsic redundancies of images and obtain a set of over-completed feature vectors. Then a supervised manifold learning algorithm (ULLELDA) is applied to project Gabor-based data and out-of-the-samples into a common low-dimensional subspace. Experiments in two FERET face databases indicate that Gabors indeed help supervised manifold learning to remarkably improve the discriminant ability of low-dimensional subspaces. © Springer-Verlag Berlin Heidelberg 2006.

关键词： Wavelet transforms

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HIERARCHICAL MODELLING IN BIOLOGY: SYSTEMATIC BUILDING OF LIMB MODELS

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IFAC Proceedings Volumes 2005年第1期38卷 49-54页

作者： Cs. Fazekas Gy. Kozmann K.M. Hangos Department of Information Systems University of Veszprém Veszprém Hungary Department of Biomedical Engineering Research Institute for Technical Physics and Materials Sciences Budapest Hungary Systems and Control Laboratory Computer and Automation Research Institute Budapest Hungary

A multi-level model, that provides a hierarchically structured description of a complex, multi-scale limb system is proposed in this paper for predicting and analyzing movement patters generated by various activation signals. The levels, the sub-models on each level and their interconnections are developed and described following a systematic modelling procedure. The computational properties (degree of freedom and differential index) of the developed model have been analyzed and a sub-model has been transformed to meet the index-one requirement for solving the resulting differential algebraic equation (DAE) model by standard methods implemented in MATLAB. The model is extensively verified against engineering expectations using parameter values found in the literature, and a good agreement was found. Parameter sensitivity analysis has also been performed.

关键词： Biomedical system model hierarchical system muscle tendon aponeurosis pennation sarcomere

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Towards NLP-driven Online-classification of Industrial Alarm Messages

Towards NLP-driven Online-classification of Industrial Alarm...

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Annual Conference of Industrial Electronics Society

作者： Yeersen Shatewakasi Birgit Vogel-Heuser Jan Wilch Victoria Hankemeier Josua Höfgen Institute of Automation and Information Systems Technical University of Munich Garching Germany Computer Science Department Autonomous Intelligent Systems Group University of Münster Münster Germany

ISBN: (数字)9781665464543

ISBN: (纸本)9781665464550

Industrial alarm systems facilitate the reliable and effective management of industrial process operations. However, the manufacturer’s fear of missing a critical fault or lacking process understanding may lead to the implementation of alarm systems that overburden operators by an enormous amount of alarms. Inadequate alarm settings and maintenance, coupled with a high volume of disturbance alarms, necessitate operators making crucial decisions within a limited time. Thus, an alarm management strategy that accurately anticipates the types of incoming alarms is needed, especially in brownfield systems where it is infeasible to simplify the underlying alarming functions. This alleviates the need for human interpretation of alarms upon arrival, allowing operators to address anomalous behaviors early. This study proposes an alarm classification approach, based on active learning, latent dirichlet allocation (LDA) topic modeling and transformer-based deep learning. It focuses on addressing these challenges through a systematic natural language processing (NLP) approach to classify and map fault messages. To demonstrate the validity of this approach, real-world alarm data from an industrial hybrid non-woven manufacturing process is used.

关键词： Industrial electronics Deep learning Systematics Manufacturing processes Alarm systems Transformers Natural language processing Maintenance Behavioral sciences Resource management

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The Method of Neural Network Control over the Process of Manufacturing Foil Solar Panels 2

The Method of Neural Network Control over the Process of Man...

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2nd IEEE International Conference on System Analysis and Intelligent Computing, SAIC 2020

作者： Sachenko, Anatoliy Ivakhiv, Orest Vyshnia, Volodymyr Grzeszczyk, Konrad Osolinskyi, Oleksandr Novosad, Stanislav Kochan, Volodymyr Nakonechnyi, Markiyan Kochan, Orest Kopania, Lukasz Kazimierz Pulaski University of Technology and Humanities in Radom Department of Informatics Radom Poland Lviv Polytechnic National University Department of Intelligent Mechatronics and Robotics Lviv Ukraine Dnipropetrovsk State University of Internal Affairs Department of Economic and Information Security Dnipro Ukraine International Vision Machinery VISORT Sp. J Radom Poland Ternopil National Economic University Department for Information Computer Systems and Control Ternopil Ukraine Ternopil National Economic University Research Institute for Intelligent Computer Systems Ternopil Ukraine Lviv Polytechnic National University Department of Computerized Automation Systems Lviv Ukraine Lviv Polytechnic National University Department of Measuring Information Technologies Lviv Ukraine

ISBN: (纸本)9781728190822

Authors have developed a method of control over one of the main technological processes of manufacturing foil solar panels, i.e., burning tracks in the layers of semiconductor material and insulation. The proposed method is based on neural networks trained directly on the control object. This eliminates the laborious process of identifying the parameters of the control object mathematical model and the impact of its error on the training outcomes. To clarify the conditions for optimizing a certain law for generating the control action by neural networks various laws of control have been simulated. It's established that laws of control can be changed according to the current situation of the control object. Simulation outcomes proofed that the most efficient is the system with the PI- controller. © 2020 IEEE.

关键词： Process control

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Parallel Saturation Based Model Checking

Parallel Saturation Based Model Checking

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International Symposium on Parallel and Distributed Computing

作者： Andr´s Voros Tam´s Szabo Attila J´mbor D´niel Darvas Akos Horv´th Tam´s Bartha Department of Measurement and Information Systems Budapest University of Technology and Economics Budapest Hungary Computer and Automation Research Institute MTA SZTAKI Budapest Hungary

Formal verification is becoming a fundamental step of safety-critical and model-based software development. As part of the verification process, model checking is one of the current advanced techniques to analyze the behavior of a system. In this paper, we examine an existing parallel model checking algorithm and we propose improvements to eliminate some computational bottlenecks. Our measurements show that the resulting new algorithm has better scalability and performance than both the former parallel approach and the sequential algorithm.

关键词： Synchronization Instruction sets Data structures Computational modeling Algorithm design and analysis Firing Parallel algorithms

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