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检索条件"任意字段=2023 International Conference on Cognitive Computing and Complex Data, ICCD 2023"

共 718 条记录，以下是261-270 订阅

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A cognitive Digital Twin Architecture for Cybersecurity in IoT-Based Smart Homes 1

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15th international conference on Sensing Technology, ICST 2022

作者： Pirbhulal, Sandeep Abie, Habtamu Shukla, Ankur Katt, Basel Norwegian Computing Center Blindern P.O. Box 114 Oslo0314 Norway Department of Risk and Security Institute for Energy Technology Halden1777 Norway Department of Information Security and Communication Technology Norwegian University of Science and Technology Gjøvik2815 Norway

ISBN: (数字)9783031298714

ISBN: (纸本)9783031298707

cognitive Digital Twin (CDT) is an extension of Digital Twin with cognitive capabilities to monitor and analyse complex and unforeseen behaviours and to ensure critical reasoning and decision-making. Thus, CDT has a potential for enhancing cybersecurity for the Internet of Things (IoT)-based applications such as smart homes. In this paper, we developed a conceptual CDT architecture for improving cybersecurity in smart homes with dynamic threat detection and mitigation capabilities. The proposed approach applies closed feedback loops between cognitive process and cybersecurity using artificial intelligence and machine learning techniques. This will allow continuous monitoring of security-related information and analytics with complex behaviours within a virtual environment. The developed approach allows security testing and simulation in the virtual world for prediction and anticipation of dynamic security threats. It also facilitates dynamic updates to the physical world of attack prevention strategies for the dynamic optimization of smart homes security. Finally, this paper discusses the applicability of the developed CDT architecture in other IoT-based critical sectors. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Internet of things

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Radar cognitive Jamming Decision Method Based on Incomplete Information Game

Radar Cognitive Jamming Decision Method Based on Incomplete ...

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2022 international conference on Statistics, data Science, and Computational Intelligence, CSDSCI 2022

作者： Feng, Luwei Liu, Songtao Xu, Huazhi Department of Information System Dalian Naval Academy Dalian China

ISBN: (纸本)9781510661325

To solve the jamming decision problem of the non-cooperative multifunctional radar in a complex electromagnetic environment, this paper proposes a radar cognitive jamming decision method based on an incomplete information game. First, the characteristics of current multifunctional radars are analyzed, and a radar jamming decision model is established based on an incomplete information game;then, after quantifying the gains of both sides by considering the jamming effect and radar anti-jamming capability, a jamming strategy selection algorithm is designed for unknown operating mode radars, and the magnitude of the jamming effect is used as the criterion for strategy seeking. Finally, the proposed method is scientifically verified utilizing simulation experiments. Compared with traditional radar jamming decision methods, this method proposed in this paper is more suitable for practical operation in terms of model design and gain quantification, and the increase in the number of radar operating modes has no impact on the accuracy of a strategy seeking;the output of jamming strategy is a pure strategy, which is accessible and apprehensible for equipment operators. © 2023 SPIE.

关键词： Decision making

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6th international conference on Innovative computing, IC 2023

6th International Conference on Innovative Computing, IC 202...

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6th international conference on Innovative computing, IC 2023

ISBN: (纸本)9789819920914

The proceedings contain 235 papers. The special focus in this conference is on Innovative computing. The topics include: Research on Visualization of Student Management System Based on Distributed Storage Technology;banking Fintech Capability Evaluation System Based on data Mining;technology Financial Service Platform Based on data Mining Algorithm;overlapping Region Extraction Method of 3D Laser Point Cloud Registration on Account of Artificial Intelligence Algorithm;smart Urban Carbon Emission Management Platform Based on Energy Big data;A Distribution Network Reconfiguration Method Considering Optimal Distribution of DG Output;a Study of Intersubjectivity in Translation Based on Communicative Behavior Theory and Computer Technology;analysis and Research on Children’s cognitive Psychological System Based on Digital Learning Terminal;analysis of E-Commerce Live Broadcast Marketing Strategy Based on Big data Algorithm;analysis of Flow data of E-Commerce Project Incubation Park Based on Computer Algorithm;Research on the Application of BIM Technology in the Whole Process Cost Management of Construction Project;analysis of Teaching Management data Based on Decision Tree Algorithm;analysis on Reasonable Planning and Design of Port Waters and Channels;ant Colony Algorithm Theory and Its Application in Control Engineering;application and Optimization of Style Transfer Algorithm in Contemporary Cultural and Creative Products;application of Ant Colony Algorithm in Chinese Language and Literature Education;Application of BP Neural Network Algorithm in Teaching Evaluation and Learning Prediction;application of Computer Aided Technology in Kindergarten Interior Design Under the "New Crown" Epidemic;application of data Mining Algorithm in Computer Mathematical Modeling;data Compression Algorithm of Power System.

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An Optimized Security Sensing Method Based on Pignistic Evidence Distance 7th

An Optimized Security Sensing Method Based on Pignistic Evid...

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7th international conference on computing, Control and Industrial Engineering, CCIE 2023

作者： Yang, Xuemei Bi, Chunyan Sichuan University Jinjiang College Meishan620860 China

ISBN: (纸本)9789819927296

In the cooperative spectrum sensing technology of cognitive radio, due to the discrete SSDF attacks of malicious users, the historical credibility is not available. In order to evaluate the credibility of evidence more accurately, an optimized security spectrum sensing method based on Pignistic evidence distance is proposed based on the spectrum sensing of D-S evidence theory. By calculating the Pignistic distance between evidences, judge whether the CU is a malicious user according to the similarity between evidences and the credibility of evidences. Finally, weighted average the BPA of trusted users, set decision rules, and conduct D-S evidence fusion. If the user is malicious, his data will not participate in the fusion. The simulation results show that this method can effectively resist the attacks of malicious users, reduce the time complexity, and get accurate results. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： cognitive radio

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A Decision Tree Model for cognitive and Functional Impairment Assessment for Alzheimer’s Disease 15th

A Decision Tree Model for Cognitive and Functional Impairmen...

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15th international conference on Soft computing and Pattern Recognition, SoCPaR 2023 and 14th World Congress on Nature and Biologically Inspired computing, NaBIC 2023

作者： Laxmaiah, Bagam Sandhya, Vooradi Rao, Chandrugonda Malleshwar Kumar, Botcha Kishore Kumar, M. Shiva Anusha, Kanneganti CMR Technical Campus Telangana Hyderabad India CMR Engineering College Telangana Hyderabad India CMR College of Engineering and Technology Telangana Hyderabad India

ISBN: (纸本)9783031810794

The functional activities questionnaire and neuropsychological scores are important tools for assessing the cognitive and functional domains of Alzheimer’s disease patients. Additionally, standardized datasets that are curated from multiple global centers are currently available and help in the computer-aided diagnosis systems development. But there are a lot of clinical tests available to gauge these scores, which makes diagnosing them is a difficult task. Additionally, the datasets have widespread problems with missing and unbalanced data. To address these problems, we suggest a machine learning-based system in this research. Scientific findings show that the decision tree performs better on the neuropsychological score following the miss forest imputation and on the functional activities questionnaire scores following the application of the synthetic minority oversampling technique. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Neurodegenerative diseases

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Classification of executive functioning performance post-longitudinal tDCS using functional connectivity and machine learning methods 20

Classification of executive functioning performance post-lon...

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20th IEEE India Council international conference, INDICON 2023

作者： Rao, Akash K Menon, Vishnu K Uttrani, Shashank Dixit, Ayushman Verma, Dipanshu Dutt, Varun Indian Institute of Technology Mandi Applied Cognitive Science Laboratory Mandi India Indian Institute of Technology Mandi School of Computing and Electrical Engineering Mandi India

ISBN: (纸本)9798350305593

Executive functioning is a cognitive process that enables humans to plan, organize, and regulate their behavior in a goal-directed manner. Understanding and classifying the changes in executive functioning after longitudinal interventions (like transcranial direct current stimulation (tDCS)) has not been explored in the literature. This study employs functional connectivity and machine learning algorithms to classify executive functioning performance post-tDCS. Fifty subjects were divided into experimental and placebo control groups. EEG data was collected while subjects performed an executive functioning task on Day 1. The experimental group received tDCS during task training from Day 2 to Day 8, while the control group received sham tDCS. On Day 10, subjects repeated the tasks specified on Day 1. Different functional connectivity metrics were extracted from EEG data and eventually used for classifying executive functioning performance using different machine learning algorithms. Results revealed that a novel combination of partial directed coherence and multi-layer perceptron (along with recursive feature elimination) resulted in a high classification accuracy of 95.44%. We discuss the implications of our results in developing real-time neurofeedback systems for assessing and enhancing executive functioning performance post-tDCS administration. © 2023 IEEE.

关键词： Electroencephalography Functional connectivity magnitude squared coherence multi-layer perceptron partial directed coherence transcranial direct current stimulation wavelet coherence

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Optimized Parallel Causal Product for Linear Transformer 3

Optimized Parallel Causal Product for Linear Transformer

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3rd international conference on Artificial Intelligence, Automation, and High-Performance computing, AIAHPC 2023

作者： Liu, Siqi BNU-HKBU United International college Zhuhai China

ISBN: (数字)9781510666580

ISBN: (纸本)9781510666573

The transformer has revolutionized Natural Language Processing and its exceptional performance has extended its application to computer vision. However, as more complex tasks arise, the demand for models to process longer sequences has increased. To address this, efficient transformers with reduced time and memory complexities have been developed. Linear transformer is an outstanding one of them with linear time complexity with input length. Causal product is the core computation of causal linear attention in linear transformer, which are commonly used to perform autoregressive tasks. However, in order to preserve the linearity, the causal products of queries are computed sequentially in Linear Transformer. We propose an innovative CUDA kernel function which allows for parallel computation of the query attention instead of sequential. Furthermore, we optimized the GPU computations of linear attention in Linear Transformer by double pipeline that decreases the time of data transmission. Our experiments demonstrate that our method achieves a 9x speedup compared to the original causal product function when implemented on a CPU. © 2023 SPIE.

关键词： Graphics processing unit

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EDGE cognitive data FUSION: FROM IN-SITU SENSING TO QUALITY CHARACTERIZATION IN HYBRID MANUFACTURING PROCESS 18

EDGE COGNITIVE DATA FUSION: FROM IN-SITU SENSING TO QUALITY ...

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ASME 18th Int Mfg Sci and Engn Conf held jointly with the 51st N Amer Res Conf / Japan-Soc-of-Mech-Engineers Int Conf on Leading Edge Mfg/Mat and Proc

作者： Hoang, Danny Mannan, Nasir ElKharboutly, Ruby Chen, Ruimin Imani, Farhad Univ Connecticut Dept Mech Engn Storrs CT 06269 USA Connecticut Ctr Adv Technol East Hartford CT USA Quinnipiac Univ Sch Comp & Engn Hamden CT USA

ISBN: (纸本)9780791887240

While hybrid additive manufacturing offers improved material properties, increased design flexibility, and reduced production time, the presence of variation in the process (e.g., torque, current, power, and tool speed), together with the impact of tool degradation (e.g., spindles, holders, and cutters) alters the surface roughness and dimensional accuracy of fabricated parts. Recently, edge sensors are coupled with machine learning techniques (e.g., feature-based support vector machines and end-toend deep neural networks) to connect process parameters with build quality. However, the lack of interpretable learning, poor sample efficiency, and low accuracy and precision limit their capabilities for reliable analysis. This paper introduces hyper-dimensional computing (HDC) to fuse load, current, torque, command speed, control differential, power, and contour deviation which provides robust, sample-efficient, and explainable learning of quality characterization. Experimental results on a real-world hybrid 5-axis CNC Deckel-Maho-Gildemeister (DMG) machine show that HDC achieves a superior 90.5% accuracy in prediction of deviation for a 25.4 mm counterbore feature using multichannel data. Comparing the difference in results with ML methods such as support vector machines, logistic regression, multinomial Naive-Bayes, multilayer perceptron, and residual neural network, HDC outperforms by 55.8%, 28.6%, 53.1%, 11.6%, and 28.0%, respectively. The proposed HDC is shown to be effective for data fusion and training with relatively few iterations and eliminates the necessity of costly and long retraining in various manufacturing processes such as 3D printing and bio-fabrication.

关键词： Hybrid additive manufacturing edge computing cognitive learning data fusion

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15th international conference on Ubiquitous computing and Ambient Intelligence, UCAmI 2023

15th International Conference on Ubiquitous Computing and Am...

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15th international conference on Ubiquitous computing and Ambient Intelligence, UCAmI 2023

ISBN: (纸本)9783031485893

The proceedings contain 88 papers. The special focus in this conference is on Ubiquitous computing and Ambient Intelligence. The topics include: Towards a Digital and Ubiquitous Ecosystem of Mobile Technology-Based Solutions to Facilitate data Management Based on Sustainable Development Goals;towards Abnormal Behaviour Detection on Elderly People at Home Through Smart Plugs and Its Relationship with Activities of Daily Living;a Framework for Managing the Experimental Evaluation of Ambient Assisted Living Systems;towards a Virtual Reality Visualization of Hand-Object Interactions to Support Remote Physical Therapy;Creating Personalized Verbal Human-Robot Interactions Using LLM with the Robot Mini;Automation of Error Recognition in Therapies Executions Based on ECogFun-VR;walkability for Active Aging: Factors and Features for an Adapted Trip Planning;predicting User Adoption and Attrition of Digital Health;a Distributed Cognition Approach to Understanding Compensatory Calendaring cognitive Systems of Older Adults with Mild cognitive Impairment and Their Care Partners;A Reinforcement Learning Algorithm for Improving the Generation of Telerehabilitation Activities of ABI Patients;Using Generative AI to Assist with Technology Adoption Assessment;"Why Did You Say That?": Understanding Explainability in Conversational AI Systems for Older Adults with Mild cognitive Impairment (MCI);proposal of a Device for Obstacle Detection Applied to Visually Impaired People;transforming Elderly Care Through Ethical and Social Evaluation of Intelligent Activity Recognition Systems in Nursing Homes;investigating Motivational Factors Influencing Users’ Consumption of Video Streaming Services: A Human Factor Perspective;translation and Validation of the AttrakDiff User Experience Questionnaire to Spanish;The Mind in Virtual Meetings: Comparing VR and Video Conferencing Environments Through Experiential Impact Assessment and EEG Analysis;human-Centered Navigation Systems: A Systematic Litera

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15th international conference on Ubiquitous computing and Ambient Intelligence, UCAmI 2023

15th International Conference on Ubiquitous Computing and Am...

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15th international conference on Ubiquitous computing and Ambient Intelligence, UCAmI 2023

ISBN: (纸本)9783031483059

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