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

共 712 条记录，以下是151-160 订阅

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'Real Worlds Illusion!' Consumer Response to Metaverse Technology Applying Flow Theory 7

'Real Worlds Illusion!' Consumer Response to Metaverse Techn...

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2023 7th international conference On computing, Communication, Control And Automation, ICCUBEA 2023

作者： Patil, Kanchan Pranay Pramod, Dhanya Pune India

ISBN: (纸本)9798350304268

Metaverse technology will revolutionize the way the hospitality and tourism industry operate and is all set to co-create transformational experiences and value addition to customers. This study explores the impact of metaverse technology application characteristics and affective/cognitive consumer characteristics on the destination visit intentions of customers through the lens of flow theory. The data collected from 371 participants were tested on a conceptual model using SEM (structural equation modelling). The study reveals that metaverse technology application features, including interactivity, informativeness, and telepresence, impacted the metaverse flow experience, however, vividness was found to be insignificant. Also, Consumers' metaverse skills and challenge levels favourably impacted metaverse flow experience, but value-add search and perceived control were found to be insignificant. Metaverse flow experience significantly influenced tourist destination visit intentions. The study's unique contribution is the blend of constructs from consumer behaviour, flow, and environmental psychology in an integrated model of metaverse tourism consumer behaviour. The study concludes with theoretical and practical implications that can benefit tourist consumers, and metaverse tourism app designers, and marketing strategies in the tourism sector. The outcome of the study will help organizations to invest in metaverse tourism to convert prospective customers and improve revenue. Policymakers and government can refer to this study for devising a strategy to promote metaverse tourism to attract tourists © 2023 IEEE.

关键词： Affective/cognitive consumer characteristics Destination visit intentions Flow theory Metaverse Metaverse technology application characteristics

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Advanced Educational Assessments: Automated Question Classification Based on Bloom's cognitive Level

Advanced Educational Assessments: Automated Question Classif...

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2023 international conference on Evolutionary Algorithms and Soft computing Techniques, EASCT 2023

作者： Vankawala, Shelin Thakkar, Amit Bhatt, Nikita Cspit Department of Computer Science & Engg Charusat India Cspit U & P U. Patel Dept. of Computer Engg Charusat India

ISBN: (纸本)9798350313413

In the contemporary education system, the quality of question papers plays a pivotal role in evaluating students' knowledge and comprehension. To ensure the validity of assessment outcomes, it is imperative to assess the quality of these question papers, taking into account factors such as question clarity, alignment with learning objectives, structural coherence, and conformity with intended educational outcomes. This study is centered around the development of a predictive model that employs Bloom's taxonomy - a framework for categorizing learning objectives - to gauge the difficulty level of questions. To optimize performance, we have harnessed the power of Bidirectional Long Short-Term Memory Network (BiLSTM), renowned for effectively preserving intricate dependencies within data. Through extensive experimentation on widely recognized datasets, our results showcased the superior accuracy of BiLSTM, with an overall accuracy rate of 80%, outperforming existing methods by a substantial margin of 5.44%. These findings represent a significant advancement in the realm of educational assessment, empowering educators with advanced machine learning techniques for more precise evaluation of students' cognitive capabilities. © 2023 IEEE.

关键词： BiLSTM Bloom's taxonomy Machine Learning Natural Language Processing

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A Novel Hybrid Backscatter Assisted cognitive Radio Networks for Maximum Throughput 9

A Novel Hybrid Backscatter Assisted Cognitive Radio Networks...

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9th international conference on Advanced computing and Communication Systems, ICACCS 2023

作者： Pradeep, G. Srividhya, G. Therasa, P.R. Shanthy, K.R. Prabha, B. Vishnu Elangovan, K. Sri Krishna College of Engineering and Technology Department of Computer Science and Engineering Tamil Nadu India Panimalar Engineering College Department of Electronics and Communication Engineering Tamil Nadu India R M K Engineering College Department Computer Science and Engineering Tamil Nadu India Loyola Institute of Technology Department Computer Science and Engineering Tamil Nadu India Jeppiaar Institute of Technology Department Artificial Intelligence and Data Science Engineering Tamil Nadu India Siddharth Institute of Engineering and Technology Department Electronics and Communication Engineering Tamil Nadu India

ISBN: (纸本)9798350397376

The research work investigates a wirelessly powered cognitive wireless communication network (CWPCN) for Internet of Things (IoT) applications that consists of a main and secondary communication system. HTT and Backscatter communication (BackCom) are two innovative methods that we propose for the secondary communications system. cognitive users have two alternatives when a main channel is overcrowded and the information receiver is unable to receive information: backscattering or collecting energy for future information transfers. Both are possibilities. To transfer information when the main channel is inactive, CUs employ bistatic scatter (BS) and high-frequency transmission (HTT) modes. To maximize secondary communication system throughput, time allocation between AB and energy harvesting and BS and HTT is examined. We find the best closed-form solution and operating modes for a particular CU circumstance. Numerical statistics show that our hybrid HTT/BackCom mode outperforms the benchmark mode. © 2023 IEEE.

关键词： Internet of things

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Underwater SLAM Implementation for a Bionic Robotic Dolphin

Underwater SLAM Implementation for a Bionic Robotic Dolphin

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2023 IEEE international conference on Real-Time computing and Robotics, RCAR 2023

作者： Ma, Shaoxuan Wang, Jian Yan, Shuaizheng Wu, Zhengxing Yu, Junzhi Chinese Academy of Sciences Laboratory of Cognitive and Decision Intelligence for Complex System Institute of Automation Beijing100190 China University of Chinese Academy of Sciences School of Artificial Intelligence Beijing100049 China Peking University State Key Laboratory for Turbulence and Complex System Department of Mechanics and Engineering Science BIC-ESAT College of Engineering China

ISBN: (纸本)9798350327182

This paper aims to implement a simultaneous localization and mapping (SLAM) algorithm for a bionic robotic dolphin in underwater simulation environment. Through combining UWSim with ROS, an underwater simulation environment is constructed through importing various environmental models including coral, tropical fish, gullies, and so on. Thereafter, as an autonomous platform for underwater SLAM, a bionic robotic dolphin with its dynamic model is particularly built in the environment to perform dolphin-like swimming. Based on the sensor information from an onboard camera and an inertial measurement unit, the VINS-Mono algorithm is employed and implemented by the robotic dolphin to position itself underwater. Extensive simulations are conducted to validate the effectiveness of the employed SLAM algorithm in various dolphin-like motions of the robotic dolphin, such as linear, circular, and spiral motions. The obtained results provide valuable guidance for the underwater SLAM research. © 2023 IEEE.

关键词： Robotics

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cognitive Disability Prediction & Analysis using Machine Learning Application 3

Cognitive Disability Prediction & Analysis using Machine Lea...

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3rd international conference on Advance computing and Innovative Technologies in Engineering, ICACITE 2023

作者： Kanna, R. Kishore Subha Ramya, V. Khafel, Asraa Ahmed Jabbar, Kadim A. Al-Tahee, Mustafa Khalid, Raed Jerusalem College of Engineering Department of Biomedical Engineering Chennai India Department of Biomedical Engineering Chennai India National University of Science and Technology Collage of Engineering Dhi Qar Iraq Al-Farahidi University Medical Laboratory Techniques Department Baghdad Iraq

ISBN: (纸本)9798350399264

A person with mild cognitive disability (MCD), a kind of memory loss that affects both memory and thinking skills, may be at an increased risk of acquiring dementia brought on by Alzheimer's disease or other neurological diseases. MCD affects between 13 and 19% of those who are 60 years of age or older. People who suffer from cognitive abnormalities should seek therapy and diagnosis as soon as they can. The major effect of MCD on the target is its effect on memory. Accurate MCD diagnosis is quite challenging with the current approaches. A hybrid approach is put forward in this study to identify MCD at an early stage. EEG data from MCD individuals and healthy controls was collected for this purpose. With the use of machine learning models including Support Vector Machines (SVM), Decision Trees (DT), k-Nearest Neighbour (KNN), and the hybrid approach ACO KNN, Renyi entropy (RE) and Discrete Wavelet Transform (DWT) characteristics were retrieved (combined Ant Colony Optimisation with k-Nearest Neighbour). The performance of the system is assessed based on an accuracy comparison with machine learning models. When compared to other models, RE and ACO KNN had an accuracy of 85.0%. © 2023 IEEE.

关键词： Discrete wavelet transforms

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Design of a Novel Autonomous Docking System With a Supporting Robotic Fish

Design of a Novel Autonomous Docking System With a Supportin...

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2023 IEEE international conference on Real-Time computing and Robotics, RCAR 2023

作者： Dong, Huijie Zhao, Chunyang Qiao, Tiezhu Wang, Jian Chen, Di Meng, Yan Yu, Junzhi Taiyuan University of Technology Key Laboratory of Advanced Transducers and Intelligent Control System Ministry of Education Taiyuan030024 China Chinese Academy of Sciences Laboratory of Cognitive and Decision Intelligence for Complex System Institute of Automation Beijing100190 China Peking University State Key Laboratory for Turbulence and Complex Systems Department of Advanced Manufacturing and Robotics College of Engineering Beijing100871 China Guangdong Ocean University College of Electronics and Information Engineering Zhanjiang524088 China

ISBN: (纸本)9798350327182

Underwater supporting robots serving as a relay of energy supplements and communication for other underwater equipment are promising for ocean exploration, development, and protection. This paper proposes a novel autonomous docking system centered on a designed supporting robotic fish named 'CourierFish'. Specifically, CourierFish is capable of docking with a surface dock station for supplying itself and docking with a seafloor platform for supporting equipment in the platform. A visual navigation scheme integrating LED and ArUco markers is presented for accurate localization. The control approach for docking motion is also illustrated. Simulations and aquatic experiments are performed to verify the feasibility of the proposed docking system. The obtained results lay a solid foundation for the construction of various underwater equipment and robot networks. © 2023 IEEE.

关键词： Fish

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data Transfer for YOLOv5 Based on Selector Network and Partial Pseudo-Labels

Data Transfer for YOLOv5 Based on Selector Network and Parti...

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cognitive computing and complex data (iccd), international conference on the

作者： Guoqiang Qu Jianchu Lin Haiyi Bian Haiping Zhou Muhammad Raees UL Haq Bo Jiang Faculty of Computer and Software Engineering Huaiyin Institute of Technology Huai’an China Faculty of Electronic Information Engineering Huaiyin Institute of Technology Huai’an China Jiangsu Eazytec Co. LTD Yixin China

ISBN: (数字)9798350352894

ISBN: (纸本)9798350352900

YOLOv5 is a widely used object detection method for its high-performance of balancing speed and accuracy. data transfer for YOLOv5 is a challenging task, as it could involve domain shift between different datasets. We propose a data transfer method for YOLOv5 based on a Selector Network and Partial Pseudo-Labeling. The backbone network of YOLOv5 is used for feature extraction, a Selector Network is employed to filter source domain outlier samples to address the domain shift issue, and Partial Pseudo-Labels are leveraged to improve classification performance in the target domain. The results show that our method improves detection accuracy by an average of 2.4% on public datasets (COCO and VOC) and our datasets, with a notable improvement of 3.1% under complex backgrounds and varying lighting conditions. It demonstrates that our method can effectively enhances the accuracy and stability of YOLOv5.

关键词： YOLO Training Accuracy Filtering Lighting data transfer Feature extraction cognitive systems Faces Batch normalization

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New Artificial Intelligence System Based on Information Processing Technology 2

New Artificial Intelligence System Based on Information Proc...

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2nd international conference on data Analytics, computing and Artificial Intelligence, ICDACAI 2023

作者： Tian, Ziye Shaanxi Institute of International Trade & Commerce School of Information Engineering Shaanxi Xi'an712000 China

ISBN: (纸本)9798350339765

Artificial intelligence (AI) technology is a product of social evolution, an important integration of scientific and technological development, and has a profound impact on people's lives and work. In recent years, countries have increased their attention to AI research. AI is not an isolated technology, and it must be based on the development of information technology. AI encompasses a wider range of knowledge domains, spanning multiple disciplines. The development of AI must be more adaptable to human needs. The networked era continues to develop and must also change. For many people, AI and Knowledge management are interconnected. As information management systems themselves become increasingly complex and contain more and more management content, without intelligent network management as a support, many problems arise in the management process. This article first introduces information processing technology and AI systems, and then explores the construction of a new type of AI system. Finally, through experiments, the power of AI's text recognition function is verified (as long as the data volume is large enough, the recall rate can reach 93.5%, approaching 100%). © 2023 IEEE.

关键词： Knowledge management

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Social cognitive Psychology Research Towards Socio-ecological Orientation Based on Big data Analysis 13th

Social Cognitive Psychology Research Towards Socio-ecologica...

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13th international conference on Frontier computing, FC 2023

作者： Yang, Zixin North Sichuan Medical College Nanchong637000 China

ISBN: (纸本)9789819994151

The role of big data analysis in social cognitive psychology is very important, but there is a problem of large analysis error. Previous psychological questionnaire analysis could not solve the problem of comprehensive analysis in social cognition, and there were few psychological scale indicators. Firstly, the big data theory is used to divide the psychological score of social cognition, and the psychological score is divided according to the degree of cognition to reduce the subjective factors in the scale analysis. Then, big data theory divides social cognitive scores into grades, forms a collection of psychological scores, and continuously analyzes psychological scores. MATLAB simulation shows that under consistent socio-ecological orientation, big data analysis methods’ accuracy and analysis time are better than those of previous psychological questionnaire analysis. © 2024, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Big data

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Proceedings - 2023 IEEE 9th international conference on Collaboration and Internet computing, CIC 2023

Proceedings - 2023 IEEE 9th International Conference on Coll...

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9th IEEE international conference on Collaboration and Internet computing, CIC 2023

ISBN: (纸本)9798350339123

The proceedings contain 16 papers. The topics discussed include: the emergence of hypergraphs in complex system analysis;RESONATE: advancing sustainability in IoT networks through smart and selective data streaming;influence pathway discovery on social media;KNNs of semantic encodings for rating prediction;understanding the behavior of ransomware: an I/O request packet (IRP) driven study on ransomware detection against execution time;scalable multimodal learning and multimedia recommendation;PRISM: a blockchain-enabled reputation-based consensus for enhancing scientific workflow provenance;enabling synergistic knowledge sharing and reasoning in large language models with collaborative multi-agents;a pro-active defense framework for IoT systems;and a Blackbox approach to profile runtime execution dependencies in microservices.

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