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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441-450 订阅

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20th international Symposium on Distributed computing and Artificial Intelligence, DCAI 2023

20th International Symposium on Distributed Computing and Ar...

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20th international Symposium on Distributed computing and Artificial Intelligence, DCAI 2023

ISBN: (纸本)9783031383175

The proceedings contain 36 papers. The special focus in this conference is on Distributed computing and Artificial Intelligence. The topics include: Using data Analytic for Social Media Posts to Optimise Recyclable Solid Waste Management Exemplary at the City of Valencia;Detection of Human Falls via Computer Vision for Elderly Care – An I3D/RNN Approach;generic Architecture for Multisource Physiological Signal Acquisition, Processing and Classification Based on Microservices;a Novel System Architecture for Anomaly Detection for Loan Defaults;enabling Distributed Inference of Large Neural Networks on Resource Constrained Edge Devices using Ad Hoc Networks;Using Neural Network to Optimize Bin-Picking in the SME Manufacturing Digital Transformation;neural Architecture Search: Practical Key Considerations;leveraging Smart City Services for Citizen Benefits Through a Unified Management Platform;step-Wise Model Aggregation for Securing Federated Learning;estimation of Occlusion Region Using Image Completion by Network Model Consisting of Transformer and U-Net;Federated Genetic Programming: A Study About the Effects of Non-IID and Federation Size;cognitive Reinforcement for Enhanced Post Construction Aiming Fact-Check Spread;chatbot Architecture for a Footwear E-Commerce Scenario;a Geolocation Approach for Tweets Not Explicitly Georeferenced Based on Machine Learning;classification of Scenes Using Specially Designed Convolutional Neural Networks for Detecting Robotic Environments;AMIR: A Multi-agent Approach for Influence Detection in Social Networks;extracting Knowledge from Testaments - An Ontology Learning Approach;AI-Based Platform for Smart Cities Urban Infrastructure Monitorization;bitcoin Price Prediction Using Machine Learning and Technical Indicators;RKTUP Framework: Enhancing Recommender Systems with Compositional Relations in Knowledge Graphs;operation of a Genetic Algorithm Using an Adjustment Function;a Classification Method for "Kawaii" Images Using Four Feat

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Multi-Request data Cache Optimization Strategy in Edge computing

Multi-Request Data Cache Optimization Strategy in Edge Compu...

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Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed computing (SNPD-Winter), ACIS international Winter conference on

作者： Futian Wang Zhimin Wu Jin Tang Chenglong Li Cheng Zhang Anhui Provincial Key Laboratory of Multimodal Cognitive Computation School of Computer Science and Technology Anhui University Hefei China School of Computer Science and Technology Anhui University Hefei China Institute of Artificial Intelligence Anhui University Hefei China

With the rapid growth in the number of mobile devices, more and more data is created and requested by users. By caching the data to the edge server, users can obtain the content they request in a closer place, which reduces the network load and improves the user experience. However, existing articles only focus on a single request of users, while users often request multiple content at one time, which leads to more complex caching scenarios. In this paper, we will study an edge data cache scenario with multiple requests, and design a cost function to optimize the cache results. In this paper, we formulate the data cache problem as a mixed integer programming problem and minimize our cost function. Extensive experiments are conducted on a real-world dataset that contains the locations of edge servers and mobile users, and the results reveal that our approach significantly outperform the baseline approaches.

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Evaluation of Trusted Channel cognitive Radio Network using WPM Method

Evaluation of Trusted Channel Cognitive Radio Network using ...

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cognitive computing and Engineering Education (ICCCEE), international conference on

作者： Monto Shrivastava Kamal Sharma Department of Mechanical Engineering GLA University Mathura India

Sensitivity to devices in distant then frequently unnoticed health, corporate complexes, and home is crucial in critical situations. Though, depending on devices data, it presents a significant challenge in informing decision-making, as standardized and trusted methods must be used. Previous efforts have focused on standardized platform modules, but these lack desirable features such as Intel SGX with consistent execution similar to TEE as Global Platform. In this paper, we propose TEE for devices to achieve reliable sensitivity including TPMs, and differentiating its use in remote devices providing common conviction assurances. We also include secure communication issues in TEE between small-sized devices with TEEs, for which we provide a secure and reliable channel protocol that enables mutual remote certification in the flow. The analysis takes into account bandwidth, duty cycle, economic cost, channel decision, cognitive radio, and data transmission as evaluation parameters. The results show that the Channel decision ranks first, while the Bandwidth and Decision Based on Economic Cost have the lowest rank.

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Supporting Co-Adaptive Machine Teaching through Human Concept Learning and cognitive Theories 25

Supporting Co-Adaptive Machine Teaching through Human Concep...

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2025 CHI conference on Human Factors in computing Systems, CHI 2025

作者： Gebreegziabher, Simret Araya Yang, Yukun Glassman, Elena L. Li, Toby Jia-Jun Department of Computer Science and Engineering University of Notre Dame Notre Dame IN United States School of Engineering and Applied Sciences Harvard University Allston MA United States

ISBN: (纸本)9798400713941

An important challenge in interactive machine learning, particularly in subjective or ambiguous domains, is fostering bi-directional alignment between humans and models. Users teach models their concept definition through data labeling, while refining their own understandings throughout the process. To facilitate this, we introduce Mocha, an interactive machine learning tool informed by two theories of human concept learning and cognition. First, it utilizes a neuro-symbolic pipeline to support Variation Theory-based counterfactual data generation. By asking users to annotate counterexamples that are syntactically and semantically similar to already-annotated data but predicted to have different labels, the system can learn more effectively while helping users understand the model and reflect on their own label definitions. Second, Mocha uses Structural Alignment Theory to present groups of counterexamples, helping users comprehend alignable differences between data items and annotate them in batch. We validated Mocha's effectiveness and usability through a lab study with 18 participants. © 2025 Copyright held by the owner/author(s).

关键词： human-AI collaboration machine teaching structural alignment theory variation theory

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1st international conference on Advances in computing Research, ACR’23

1st International Conference on Advances in Computing Resear...

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1st international conference on Advances in computing Research, ACR’23

ISBN: (纸本)9783031337420

The proceedings contain 53 papers. The special focus in this conference is on Advances in computing Research. The topics include: HealthCare Text Analytics Using Recent ML Techniques;emotion Recognition Techniques with IoT and Deep Learning Technologies;hybrid Capsule Network for Hyperspectral Image Unmixing and Classification;an Artificial Intelligence Peer-To-Peer Car Repair Platform;passive Operating System Fingerprinting Analysis Using Artificial Intelligence Techniques;a Highly Efficient Computer Vision Approach for Tennis Ball Retrieval with Limited Computational Power;work Disability Risk Prediction with Text Classification of Medical Reports;A Comparison of LSTM and GRU for Bengali Speech-to-Text Transformation;advanced Traffic Management System for Smart Cities;taxonomy for an Automated Sleep Stage Scoring;explainability of Machine Learning in Work Disability Risk Prediction;a Power Efficient Solution to Determine Red Blood Cell Deformation Type Using Binarized DenseNet;augmented Reality for cognitive Impairment and Dementia;enhancing the Tourism Experience Using Mobile Augmented Reality: Geo-Visualization Techniques;a Taxonomy of Secure data Transmission Techniques: Preventing Sybil Attacks in Vehicular Ad Hoc Networks;detecting Spyware in Android Devices Using Random Forest;statistical Approaches to File Fragment Analysis;analysis of Intrusion Detection Using Ensemble Stacking-Based Machine Learning Techniques in IoT Networks;smart Grid Security: A Systematic Literature Review;analysis of Malicious Intruder Threats to data Integrity;convolutional Neural Networks Based Classification of Mammograms;a Review of Cybersecurity Advancements in Unmanned Aerial Vehicle;open Voting Client Architecture and Op-Ed Voting for Secret Ballot Elections;mobility-Aware Workload Distribution and Task Allocation for Mobile Edge computing Networks;a Comparative Analysis of Performance and Usability on Serverless and Server-Based Google Cloud Services;Multi-objective VNF Place

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Secure Communication Scheme for IRS-UAV Enabled cognitive Network

Secure Communication Scheme for IRS-UAV Enabled Cognitive Ne...

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Intelligent Communications and computing (ICC), international conference on

作者： Zhen Wang Zhiyue Li Jiajin Wen Meng Zhao Xinyan Zhou Lisu Yu School of Information Engineering Nanchang University NanChang China

In this paper, the secure communication model is considered in cognitive relay network. An intelligent reflecting surface (IRS) which is deployed on unmanned aerial vehicle (UAV) is applied to cognitive relay of communication link between secondary internet of things (SIoT) devices and secondary user (SU). However, the presence of secondary eavesdropper (SE) causes security issue for cognitive communication network. Therefore, the problem of average secrecy rate maximization is formulated through the joint design of UAV trajectory, SIoT signal transmission power and IRS passive beamforming without affecting the communication quality among primary users (PUs). Nevertheless, it is infeasible to obtain optimal solution directly for original problem which is non-convex. An efficient algorithm is proposed to solve complex and non-convex problem. Simulation result demonstrates that the proposed algorithm can enhance the average secrecy rate more effectively, and can maximally rise by approximately 108% in comparison with other schemes.

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data Visualization Analysis of Metacognition in BE Problem Solving: Re-categorization and Its Implications

Data Visualization Analysis of Metacognition in BE Problem S...

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IEEE international conference on Cloud computing and Big data Analysis (ICCCBDA)

作者： Xueyan Yin Guihang Guo School of English Language and Culture South China Business College Guangdong University of Foreign Studies Guangzhou China School of English for International Business Guangdong University of Foreign Studies Guangzhou China

Widely acknowledged as knowledge and cognition about cognitive phenomena, metacognition has become a successful tool for researchers to investigate problem solving and other thinking processes in the instructional domain. However, much of the work on metacognition has studied these constructs piecemeal and mostly qualitatively with little evidence found about cognition in business English problem solving. In light of this, by statistically based re-categorization of metacognition in business English context, we investigated the interplay of metacognitive aspects in BE problem solving. 105 third-year college students participated in the study. Metacognitive aspects (metacognitive experiences, metacognitive knowledge and metacognitive regulation) were quantitatively measured with statistical tools of SPSS, AMOS and Wordclouds, in which questionnaires and semi-structured interviews were employed to further explore 2 questions: (1) What are the prominent factors constituting BE metacognition? (2) To what extent is metacognition positively related to BE problem solving and perceived performance? Three categories of BE metacognition are identified and the data visualization analysis indicate a complex interplay of metacognition in BE problem solving, in which metacognitive knowledge and metacognitive regulation play a statistically significant role.

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EEG-Based Emotion Recognition Using Similarity Measures of Brain Rhythm Entropy Matrix 14th

EEG-Based Emotion Recognition Using Similarity Measures of B...

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14th international conference on Brain Inspired cognitive Systems, BICS 2024

作者： Feng, Guanyuan Wang, Peixian Wu, Xinyu Ren, Ximing Ling, Chen Huang, Yuesheng Wang, Leijun Lv, Jujian Li, Jiawen Chen, Rongjun School of Computer Science Guangdong Polytechnic Normal University Guangzhou 510665 China Anhui Provincial Key Laboratory of Multimodal Cognitive Computation Anhui University Hefei 230601 China Guangdong Provincial Key Laboratory of Intellectual Property and Big Data Guangdong Polytechnic Normal University Guangzhou 510665 China

ISBN: (纸本)9789819628810

Constructing the Brain Rhythm Entropy Matrix (BREM) as a feature for emotion recognition is feasible due to the correlation between brain rhythm activities and arousal/valence levels, as well as the effectiveness of entropy in quantifying such activities. Besides, similarity, a vital metric in bioinformatics, measures the degree of resemblance between internal elements. Building on these foundations, this paper introduces an emotion recognition method that leverages the similarity measures of BREM derived from EEG signals. The results using the DEAP database indicate that the proposed method achieves an accuracy range of 75% to 92% by employing the optimal single-channel data for emotion recognition. Furthermore, significant individual differences were observed in selected channels and time windows for emotion recognition. Such findings not only offer an innovative manner for EEG-based emotion recognition through BREM and similarity measures but also provide advances for designing portable emotion computing devices in the future. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Brain Rhythm Entropy Matrix (BREM) EEG Emotion Recognition Similarity Measures

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Designing Energy Routing Protocol with Energy Consumption Optimization in cognitive Radio Networks 1

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8th international conference on Emerging Research in computing, Information, Communication and Applications, ERCICA 2023

作者： Reddy Bolla, Dileep Ramesh Naidu, P. Jijesh, J.J. Vinay, T.R. Srikanth Palle, Satya Keshavamurthy Department of CSE Nitte Meenakshi Institute of Technology Yelahanka Bangalore India Department of E&CE Sri Venkateshwara College of Engineering Bangalore India Department of AIDS M S Ramaiah Institute of Technology Bangalore India Department of Electronics and Communications Atria Institute of Technology Bangalore India

ISBN: (数字)9789819976331

ISBN: (纸本)9789819976324

As the technology is progressing rapidly, the spectrum sensing and the mobility of wireless nodes have become a concern to address the issues in cognitive radio networks (CRNs). We propose an energy optimization technique by using the residual energy concept, and a new routing protocol EERP (Energy Efficient Routing Protocol) is being proposed with the terminal node to address the effects of energy resource limitations for CRN and to improvise network routing. The EERP protocol aids in selecting the optimum path from nearby nodes among potential transmission channels in the proposed work. The protocol’s local route maintenance technique will be strengthened if the path has been damaged. This intern decreases retransmission and boosts routing effectiveness even more. Additionally, by choosing the fault path as a result of energy exhaustion, this can stop the link transmission process. The low-energy adaptive clustering hierarchy (LEACH) technique has undergone a thorough investigation and comparison. Based on the results, it is concluded that the EERP can balance the load, safeguard low-energy nodes, lengthen network survival times, and further cut down on packet loss rates and data delivery packet delays. © 2024, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Energy efficiency

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2nd international Congress of Electrical and Computer Engineering, ICECENG 2023

2nd International Congress of Electrical and Computer Engine...

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2nd international Congress of Electrical and Computer Engineering, ICECENG 2023

ISBN: (纸本)9783031527593

The proceedings contain 28 papers. The special focus in this conference is on Electrical and Computer Engineering. The topics include: Forecasting the Number of Passengers in Rail System by Deep Learning Algorithms;viola–Jones Method for Robot Vision Purpose: A Software Technical Review;Comparing ChatGPT Responses with Clinical Practice Guidelines for Diagnosis, Prevention, and Treatment of Diabetes;ML-Based Optimized Route Planner for Safe and Green Virtual Bike Lane Navigation;pre-Trained Variational Autoencoder Approaches for Generating 3D Objects from 2D Images;enhancing Ground Vehicle Route Planning with Multi-Drone Integration;breast Cancer Diagnosis from Histopathological Images of Benign and Malignant Tumors Using Deep Convolutional Neural Networks;enhancing Skin Lesion Classification with Ensemble data Augmentation and Convolutional Neural Networks;open-Source Visual Target-Tracking System Both on Simulation Environment and Real Unmanned Aerial Vehicles;Semi-supervised Deep Learning for Liver Tumor and Vessel Segmentation in Whole-Body CT Scans;legacy Versus Algebraic Machine Learning: A Comparative Study;Comparison of Textual data Augmentation Methods on SST-2 dataset;machine Learning-Based Malware Detection System for Android Operating Systems;A Comparative Study of Malicious URL Detection: Regular Expression Analysis, Machine Learning, and VirusTotal API;an Efficient Technique Based on Deep Learning for Automatic Focusing in Microscopic System;parallel Modeling of complex Dynamic Systems in the Vector-Matrix Form;a Smart Autonomous E-Bike Fail-Safe System;Parallel Implementation of Discrete Cosine Transform (DCT) Methods on GPU for HEVC;mathematical Models and Methods of Observation and High-Precision Assessment of the Trajectories Parameters of Aircraft Movement in the Infocommunication Network of Optoelectronic Stations.

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