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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361-370 订阅

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Prediction of Influenza A Cases in Tropical Climate Country using Deep Learning Model 2

Prediction of Influenza A Cases in Tropical Climate Country ...

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2nd IEEE National Biomedical Engineering conference, NBEC 2023

作者： Abd Rahim, Muhamad Sharifuddin Yakub, Fitri Omar, Mas Abd Ghani, Rasli Dhamanti, Inge Sivakumar, Soubraylu Universiti Teknologi Malaysia Wee Laboratory Malaysia-Japan International Institute of Technology Kuala Lumpur Malaysia Universiti Teknologi Malaysia Malaysia-Japan International Institute of Technology Department of Electronic System Engineering Kuala Lumpur Malaysia Faculty of Public Health Department of Health Policy and Administration Surabaya Indonesia Srm Institute of Science and Technology Computing Technologies Chennai India

ISBN: (纸本)9798350338546

Influenza remains a significant public health concern particularly in tropical climate countries. Accurate prediction of influenza cases is crucial for effective resource allocation and public health planning. This study aimed to design and evaluate deep learning models for the monthly prediction of influenza A cases in a tropical climate country specifically Malaysia. The models considered both univariate and multivariate input configurations incorporating temperature and humidity variables. The study utilized a dataset spanning from January 2006 to December 2019 with training data from January 2006 to December 2016 and test data until December 2019. Various deep learning models such as RNN, LSTM, complex LSTM, GRU, Transformer and Informer were implemented and evaluated. The results demonstrated that the RNN variants specifically LSTM and GRU consistently outperformed the transformer and informer models for both univariate and multivariate prediction. The shorter input sequences (2 months) yielded better performance compared to longer sequences (12 months) with mean square error (MSE) of 0.0069, capturing more relevant temporal patterns and dependencies. The deep learning models produce a better ability to capture complex relationships and temporal patterns in the data. The findings highlight the effectiveness of the RNN variants and the impact of input configurations and sequence lengths on predictive performance. These findings provide valuable insights that can support public health planning and decision-making processes. dataset can be obtained from the https://***/joqxA. © 2023 IEEE.

关键词： Forecasting

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Enhancing cognitive Radio Networks using AI-Driven Stackelberg Game Strategies for Proactive Susceptibility Management 2

Enhancing Cognitive Radio Networks using AI-Driven Stackelbe...

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2nd IEEE international conference on Communication, Security and Artificial Intelligence, ICCSAI 2023

作者： Singh, Arjun Bhandari, Prabhakar Singh, Aishwarya Kumar, V. Mathan Subha, E. Nigam, Shalini Y. Dev Bhoomi Uttarakhand University Electronics and Communications Engineering Uttarakhand 248007 India School of Engineering & Technology K. R. Mangalam University Department of Mechanical Engineering Haryana Gurugram122103 India Invertis University Department of Computer Science & Engineering Uttar Pradesh Bareilly243123 India Karpagam Academy of Higher Education Department of Commerce Coimbatore641021 India Karpagam College of Engineering Department of Science and Humanities Coimbatore641032 India Vishwakarma Institute of Information Technology Pune India

ISBN: (纸本)9798350369960

In the rapidly advancing field of wireless communications, the concept of cognitive Radio Network Systems (CRNS) has been enriched by the emergence of a new paradigm known as Collective CRNS Channels. This approach, stemming from the development of Federated Dialogue and Device-to-Device (D2D) systems, posits that entities can serve as collaboration beacons, thereby securing temporal and spatial rights for spectrum sensing. Contemporary research predominantly focuses on the spectrum market dynamics, delving into aspects such as spectrum leasing and trading within economic frameworks. However, these investigations have typically presupposed passive roles for relay nodes, neglecting the scenario where active intermediary nodes may opt out of collaboration with primary users due to the incentives presented by a spectrum market. This study adopts a novel approach, employing a Dynamic Stochastic General Game (DSGG) model to scrutinize the interplay between secondary users' inclinations for bandwidth leasing versus collaborative engagement. This model facilitates a deeper understanding of the strategic behaviors of users under the influence of market forces and the allocation of spectrum rights. The findings of this research underscore the necessity of integrating economic considerations into the architecture of future radio spectrum auctions. It is demonstrated that the economic behaviors of secondary users, governed by a preference for spectrum leasing, introduce complex variables that must be accounted for in the design of collaborative CRNS channels. This study paves the way for more nuanced and economically informed models in the arena of spectrum allocation and management, a critical component in the landscape of computer science, AI, ML, data mining, and wireless communication systems. © 2023 IEEE.

关键词： Adaptive Wireless Communication Systems cognitive Radio Optimization Network Performance Enhancement Stackelberg Game Theory Susceptibility Management

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Understanding Users’ Decision-Making on Privacy Disclosure from a Configurational Perspective Perceived Values, Privacy Concerns, cognitive Style, and Trust 19th

Understanding Users’ Decision-Making on Privacy Disclosure ...

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19th international conference on Wisdom, Well-Being, Win-Win, iconference 2024

作者： Chen, Xiaoyu Yang, Ruoxi School of Cultural Heritage and Information Management Shanghai University Shanghai China

ISBN: (纸本)9783031578496

Based on the privacy calculus model, users traditionally made decisions about privacy disclosure by weighing perceived values against privacy concerns. However, recent studies indicate that users’ cognitive style and trust also play significant roles in a social media context. This study examines how these factors collectively influence users’ privacy disclosure behavior from a configurational perspective. Through an online survey, we collected data from 452 respondents on a Chinese social media platform. The results reveal that users’ decision-making on privacy disclosure is a complex process with various configurations. For individuals with a field-dependent cognitive style, cognitive style is more important than the trade-off between perceived values and privacy concerns. On the other hand, for field-independent individuals, decisions are not only influenced by the trade-off between perceived values and privacy concerns but also by trust. We finally discuss the theoretical and practical implications of these findings. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.

关键词： Decision making

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cognitive computing for Natural Language Processing (NLP) and Understanding Medical Imaging Narratives

Cognitive Computing for Natural Language Processing (NLP) an...

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Communication, Security and Artificial Intelligence (ICCSAI), international conference on

作者： Himanshu Makhija Centre for Interdisciplinary Research in Business and Technology Chitkara University Institute of Engineering and Technology Chitkara University Punjab India

In recent years, the intersection of cognitive computing and natural language processing (NLP) has emerged as a pivotal area of research, promising transformative advancements in medical imaging. This paper delves into the integration of cognitive computing techniques with NLP to enhance the interpretation and understanding of complex medical narratives. We introduce a novel framework that leverages the cognitive capabilities of machines to process, analyze, and comprehend vast amounts of unstructured medical text. Our approach employs deep learning architectures and semantic analysis to extract clinically relevant information from radiology reports, patient histories, and other textual data sources. Preliminary results indicate a significant improvement in the accuracy and efficiency of medical image annotations, leading to more precise diagnostic insights. Furthermore, the system demonstrates an adeptness at understanding intricate medical jargons, abbreviations, and context-dependent interpretations. This research not only underscores the potential of cognitive computing in revolutionizing medical imaging but also sets a precedent for its application in other domains requiring nuanced language understanding.

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What Affects the Adoption of Metaverse in Education? A SEM-based Approach 20

What Affects the Adoption of Metaverse in Education? A SEM-b...

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20th international Joint conference on Computer Science and Software Engineering, JCSSE 2023

作者： Rohan, Rohani Roy, Pranab Vanijja, Vajirasak Funilkul, Suree Mukherjee, Subhodeep Pal, Debajyoti School of Information Technology King Mongkut's University of Technology Thonburi Bangkok Thailand Jk Laxmipat University Department of Computer Science and Engineering Jaipur India Department of Operations Management Visakhapatnam India Kmutt Innovative Cognitive Computing Research Center Bangkok Thailand

ISBN: (纸本)9798350300505

Metaverse is an emerging 3D digital space that augments the real world and the virtual world. It has been envisioned to be the trendsetter for future education having tremendous potential. However, the success of any new technology depends on its mass adoption and widespread societal diffusion. Therefore, it becomes important to understand the factors that can lead to its success by ensuring widespread adoption. In this work, we investigate the different psychological gratifications of the educational usage of Metaverse under the lens of the Uses and Gratification (UGT) theory. Particularly, we propose and test a research model by using the Structural Equation Modelling (SEM) approach by considering four fundamental psychological gratifications of autonomy, achievement, affiliation, and dominance, together with two additional factors of hedonic motivation and student personality. data is collected from two Asian universities, and results show the importance of autonomy, hedonic motivation, and personality in predicting Metaverse adoption. © 2023 IEEE.

关键词： Motivation

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Developing and Accessing Policies in Maritime Education Using Multicriteria Analysis and Fuzzy cognitive Map Models 3rd

Developing and Accessing Policies in Maritime Education Usin...

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3rd international conference on Novel and Intelligent Digital Systems, NiDS 2023

作者： Karnavas, Stefanos Kardaras, Dimitrios Barbounaki, Stavroula Troussas, Christos Tselenti, Panagiota Kyriazis, Athanasios Department of Statistics and Insurance Science University of Piraeus Piraeus Greece School of Business Department of Business Administration Athens University of Economics and Business Athens Greece Department of Midwifery University of West Attica Egaleo Greece Department of Informatics and Computer Engineering University of West Attica Egaleo Greece

ISBN: (纸本)9783031441455

The development and assessment of education policies in maritime is a complex task as it requires the consideration of several factors such as stakeholders’ views, infrastructure availability, lecturers’ potential, and motivation. Besides, the effectiveness of education policies can only be assessed at a later time after decisions have been made and investments have been implemented. Thus, the post development of education policies may be difficult to reverse let alone that new initiatives and directions are prone to the same difficulties and inefficiencies. This paper addresses the need for the design and assessment of alternative education policies scenarios before any actions are taken by proposing a hybrid methodological approach, utilising multicriteria analysis and fuzzy cognitive maps. This research analyses data collected from maritime academy students and staff in Greece. The proposed methodology provides the means for the development of fuzzy intelligent systems that allow education policy makers to develop education policies and assess their impact on education quality, student satisfaction and satisfaction of maritime companies. The results can be useful for both researchers and education policy makers. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Fuzzy cognitive Maps

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cognitive Architecture of a System to Replicate Human Strategic Decision-Making 7th

Cognitive Architecture of a System to Replicate Human Strate...

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7th international Scientific conference on Intelligent Information Technologies for Industry, IITI 2023

作者： Tselykh, Alexander Tselykh, Larisa Southern Federal University Nekrasovskii 44 Taganrog347922 Russia Rostov State University of Economics Initsiativnaya 48 Taganrog347936 Russia

ISBN: (纸本)9783031437885

This article addresses the problem of creating an artificial intelligence (AI) system to replicate human management decision-making in the development of control impact strategies using cognitive causal models (CMs) of complex systems (sociohumanitarian, political). The basis of replication is the research and development of a cognitive architecture as a fixed base of closely related mechanisms that underlie intelligent behavior. The cognitive architecture of the proposed system is based on the hypothesis that human management decision-making is based on a general (abstract) idea of the system as a whole (mental image) in the paradigm of causal relations, which is created as a result of a special type of mental perception. This special kind of perception is the ability of a person to create mental images using generalization and abstract thinking. We present these mental images as professional knowledge that a person acquires through experience and learning throughout his life, and which is stored in the human brain. The acquisition of professional knowledge for storage in long-term memory will be carried out by accessing the vast database of world knowledge on the Internet (initial knowledge), processing the discovered data into CM, and storing this new knowledge. The decision procedure retrieves the CM stored in the declarative semantic memory, compares it with the current situation, and updates this CM representation using the CM learning mechanism. Further, the solution of the optimization problem creates ranked possible scenarios of control actions. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023.

关键词： Decision making

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AQ-GT: a Temporally Aligned and Quantized GRU-Transformer for Co-Speech Gesture Synthesis 23

AQ-GT: a Temporally Aligned and Quantized GRU-Transformer fo...

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25th international conference on Multimodal Interaction, ICMI 2023

作者： Voß, Hendric Kopp, Stefan Social Cognitive Systems Group Bielefeld University Germany

ISBN: (纸本)9798400700552

The generation of realistic and contextually relevant co-speech gestures is a challenging yet increasingly important task in the creation of multimodal artificial agents. Prior methods focused on learning a direct correspondence between co-speech gesture representations and produced motions, which created seemingly natural but often unconvincing gestures during human assessment. We present an approach to pre-train partial gesture sequences using a generative adversarial network with a quantization pipeline. The resulting codebook vectors serve as both input and output in our framework, forming the basis for the generation and reconstruction of gestures. By learning the mapping of a latent space representation as opposed to directly mapping it to a vector representation, this framework facilitates the generation of highly realistic and expressive gestures that closely replicate human movement and behavior, while simultaneously avoiding artifacts in the generation process. We evaluate our approach by comparing it with established methods for generating co-speech gestures as well as with existing datasets of human behavior. We also perform an ablation study to assess our findings. The results show that our approach outperforms the current state of the art by a clear margin and is partially indistinguishable from human gesturing. We make our data pipeline and the generation framework publicly available. © 2023 ACM.

关键词： Behavioral research

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22nd international conference on Informatics in Economy, IE 2023

22nd International Conference on Informatics in Economy, IE ...

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22nd international conference on Informatics in Economy, IE 2023

ISBN: (纸本)9789819969593

The proceedings contain 36 papers. The special focus in this conference is on Informatics in Economy. The topics include: Models for Determining the Reached Level of Digitalization;analyzing the Antecedents of Fake News Sharing in Online Social Networks;considerations About the Regulatory Framework of Cryptocurrency;attitudes Toward Digital Transformation in Economics Education;regional Development and the Role of Public Sector Digital Maturity;enhancing the Financial Sector with Quantum computing: A Comprehensive Review of Current and Future Applications;an Application of the Flexible Best–Worst Method to Weighting Internet of Things Security Requirements;main Characteristics and Cybersecurity Vulnerabilities of IoT Mobile Devices;personalized Big data Access: Value for Medical Staff;an Analysis About Smartphone Usage and Security in Europe: Trends and Insights;a Formal Intelligent Metric System for Measuring Cyber Security Maturity;impact of Personalization on Improving a Chatbot’s Performance. Case Study for a Banking Virtual Assistant;a Citation-Based Scientometric Analysis of Published Articles from Bucharest University of Economic Studies;Ship Detection Using SAR—An Integration of Geographic Systems;Develop a Machine Learning Life Cycle in Oracle Accelerated data Science (ADS) SDK;Improving Programming Activities Using ChatGPT: A Practical Approach;cybernetics Analysis of the Circular Economy from Romania;modeling Literary Preferences Using complex Networks and Centrality Measures;Managing Tourism Crises: An MDP-Based Approach for Optimal Investment Strategies;multiple Behavior Patterns in Ad-Related Web Traffic of Humans and Bots;The Impact of OFDI, Financial Development, and Green Credit on Carbon Reduction;index Arbitrage Systematic Trading Strategy Value Proposition;production and Transportation Model with Environmental Pollution Constraints.

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cognitive data FUSION FOR IMPROVING FLEXIBILITY IN SMART HOMES 27

COGNITIVE DATA FUSION FOR IMPROVING FLEXIBILITY IN SMART HOM...

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27th international conference on Electricity Distribution, CIRED 2023

作者： Redhu, Surender Raja, Rameez Nygård, Heidi S. Bremdal, Bernt A. Smart Innovation Norway Norway østfold University College Norway NMBU Norway University of Tromsø Norway

ISBN: (纸本)9781839539596

With the advancements in information and communication technology, accurate monitoring ofenergy consumption in smarts home has becomefeasible. This results in improved flexibility at household level by optimizing the appliances' scheduling. However, this is challenging at the same time due to uncertainties in energy' consumption, and therefore demands a highly accurate forecasting ofappliance-level energy consumption. In this context, this work presents a scheme where the energy consumption patterns ofmultiple appliances are exploredjointly. The energy' consumption ofseveral appliances which are recorded as a time-series data, are clustered based on a well-established algorithm named k-shape. Utilizing k-shape time-series clustering algorithm, the consumption relation between different appliances is observed by computing the cross-correlation phenomenon which provides several clusters of appliances. All the appliances ofa particular cluster show similarity' in their energy consumption pattern. Further, the output from k-shape algorithm is utilized to forecast the consumption ofa particular appliance in a cluster by utilizing the time-series energy consumption of other appliances of that cluster. We performed the clustering and forecasting experiments on a real dataset of 43 appliances in a household. We observed improved day-ahead forecasting performance utilizing the proposed scheme which motivates us to implement it in practical scenarios to enhanceflexibility in smart homes. © The Institution of Engineering and Technology 2023.

关键词： Energy utilization

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