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15th IEEE International Conference on Cognitive Infocommunications, CogInfoCom 2024

作者： Horváth, Ildikó Sudár, Anna Baranyi, Péter Corvinus Institute for Advanced Studies Institute of Data Analytics and Information Systems Corvinus University of Budapest Budapest Hungary Hungarian Research Network HUN-REN Budapest Hungary

ISBN: (纸本)9798350378245

This paper examines the trends in the adoption of VR technologies for online conferences, comparing the use of simple 2D online meeting software with more sophisticated VR systems. The authors aim to evaluate the effectiveness of 2D online meeting platforms (e.g., Zoom, Teams) versus advanced VR systems (e.g., AltspaceVR, Horizon Workrooms) in virtual conference settings. The study highlights the limitations of 2D platforms in terms of engagement and interaction while showcasing the immersive benefits of VR environments. The goal is to provide a framework for understanding the evolving landscape of virtual conferences and leveraging VR technologies to enhance overall conference effectiveness. Case studies from the 2020 and 2021 conference cycles illustrate the practical implementation of VR environments, demonstrating how these spaces facilitate the entire conference process. Key findings indicate that VR platforms significantly improve participant engagement and interaction compared to 2D platforms. The paper also discusses hybrid models that combine 2D and VR elements, offering flexibility and maximizing participant engagement throughout the Pre-Conference, In-Conference, and Post-Conference phases. © 2024 IEEE.

关键词： Virtual environments

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Presence and Navigational Experience in Desktop Virtual Reality 15

Presence and Navigational Experience in Desktop Virtual Real...

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15th IEEE International Conference on Cognitive Infocommunications, CogInfoCom 2024

作者： Berki, Borbála Corvinus Institute for Advanced Studies Institute of Data Analytics and Information Systems Corvinus University of Budapest Budapest Hungary Hungarian Research Network HUN-REN Budapest Hungary

ISBN: (数字)9798350378245

ISBN: (纸本)9798350378245

This study explores how previous experience and navigational experience relate to the sense of presence in desktop virtual reality environments. The research aims to explore the correlation between user familiarity with VR software, the perceived naturalness of navigation, and presence. A total of 112 participants utilized the MaxWhere desktop VR platform in three separate studies and completed the Igroup Presence Questionnaire (IPQ) and a navigational experience survey. Results indicate a positive correlation between previous VR experience and the sense of presence. Additionally, users who found navigation more intuitive reported higher levels of presence. These findings underscore the importance of user proficiency and seamless navigation in enhancing VR immersion. © 2024 IEEE.

关键词： Virtual environments

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Approximations of Euler-Maxwell systems by drift-diffusion equations through zero-relaxation limits near the non-constant equilibrium

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Science China Mathematics 2025年第5期68卷 1051-1078页

作者： Rui Jin Yachun Li Liang Zhao School of Mathematical Sciences Shanghai Jiao Tong UniversityShanghai200240China CMA-Shanghai MOE-LSCand SHL-MACShanghai Jiao Tong UniversityShanghai200240China Mathematical Modelling&Data Analytics Center Oxford Suzhou Centre for Advanced ResearchSuzhou215123China

Due to extreme difficulties in numerical simulations of Euler-Maxwell equations,which are caused by the highly complicated structures of the equations,this paper concerns the simplification of the Euler-Maxwell system through the zero-relaxation limit towards drift-diffusion equations with non-constant doping *** carry out the global-in-time convergence analysis by establishing uniform estimates of solutions near nonconstant equilibrium regarding the relaxation parameter and passing to the limit by using classical compactness ***,we generalize the stream function method to the non-constant equilibrium case,and together with the anti-symmetric structure of the error system and an induction argument,we establish globalin-time error estimates between smooth solutions to the Euler-Maxwell system and those to the drift-diffusion system,which are bounded by some power of the relaxation parameter.

关键词： global convergence rate Euler-Maxwell system Euler-Poisson system non-constant equilibrium state zero-relaxation limit

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Virtual and Augmented Reality in Education Based on CogInfoCom and cVR Conference Insights 15

Virtual and Augmented Reality in Education Based on CogInfoC...

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15th IEEE International Conference on Cognitive Infocommunications, CogInfoCom 2024

作者： Berki, Borbála Sudár, Anna Corvinus Institute for Advanced Studies Institute of Data Analytics and Information Systems Corvinus University of Budapest Budapest Hungary Hungarian Research Network HUN-REN Budapest Hungary

ISBN: (纸本)9798350378245

This paper investigates educational virtual and augmented realities within the Cognitive Infocommunications (CogInfoCom) and Cognitive Aspects of Virtual Reality (cVR) conference series. By analyzing trends from 2016 to 2023, the study identifies key themes and technological differences in the use of VR and AR for different educational purposes. The findings highlight a significant rise in VR-based educational research, with a notable focus on higher education and professional training. The paper also examines the prevalence of different VR devices, such as desktop VRs and head-mounted displays, and their application in safety training and other educational scenarios. Through a detailed review of conference publications, this study aims to provide insights into the evolving landscape of VR and AR in education and their potential to enhance learning experiences. © 2024 IEEE.

关键词： Virtual environments

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A Novel Approach for Customer Segmentation and Product Recommendation to Boost Sales using Machine Learning

A Novel Approach for Customer Segmentation and Product Recom...

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International Conference on Computing for Sustainable Global Development (INDIACom)

作者： Anik Chakraborty Krishnendu Dey Sayantani Ghosh Raktim Chakraborty Indranil Mitra Prasun Nandy Data & Analytics Advanced Analytics PwC India Kolkata India

Personalized marketing is one of the most important marketing strategies which drives sales for a business by recommending the right products to the right customers. With the growing volume of consumers, it becomes necessary to divide them into suitable groups to take appropriate action for the correct set of customers. The prime objective of this study is to segment the customers into meaningful groups, suggest different marketing strategies for various segments, and recommend suitable products for each customer within the groups. This paper analyses historical sales and customer interaction data of the business to derive the right attributes. This study has used $\mathbf{K}$ -Means clustering, an unsupervised machine learning algorithm, to obtain five separable clusters with a silhouette score of 0.57. For product recommendation, a voting ensemble-based recommendation system has been used to suggest up to the top 10 products for each customer. The ensemble method consists of four techniques: user-based collaborative filtering, LightFM algorithm, KNNWithMeans algorithm, and neural network. The paper aims to amalgamate customer segmentation and product recommendation problem statements for developing a single solution to help businesses design personalized marketing strategies.

关键词： Machine learning algorithms Computational modeling Neural networks Clustering algorithms Stars Predictive models Prediction algorithms

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Exploring the Intersection of IoT and Blockchain: An Analysis of Security and Privacy Risks

Exploring the Intersection of IoT and Blockchain: An Analysi...

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2023 International Conference on Computer Communication and Informatics, ICCCI 2023

作者： Ashok, Harishma Ganesan, Swathi Somasiri, Nalinda PSG Institute of Advanced Studies Data Analytics Coimbatore India York St John University Department of Computer Science London United Kingdom

ISBN: (纸本)9798350348217

Internet of things (IoT) is one of the leading technologies of transforming the internet into the next level. Security of IoT is becoming a major challenge and its measures of stopping these insecurities have been developing. Improving IoT security is important since IoT provides a great environment for systems in the industrial world and other several applications. The challenges need to be addressed so that consumer's data can be safe. Measures available are to improve the protection of access by unauthorized persons, providing a safe way to transfer data, and ensuring synchronization of the system. Blockchain has also provided a safe way for IoT devices, each device is given the public key, IoT devices scramble and send the message dependent on the public key of the objective device so just the objective device can unscramble the message. © 2023 IEEE.

关键词： Internet of things

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Domain Model Enrichment with Deep Inductive Transfer from Automotive data

Domain Model Enrichment with Deep Inductive Transfer from Au...

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International Conference on Prognostics and Health Management, PHM

作者： Dnyanesh Rajpathak Advanced Analytics Center of Expertise Enterprise Data Analytics and Insights General Motors Warren MI USA

ISBN: (数字)9798350374476

ISBN: (纸本)9798350374483

In this paper, we propose a deep transfer learning model that automatically learns domain ontology from different automotive datasets. Equipment safety is one of the key priorities for original equipment manufacturers (OEMs). It is important to preempt and quickly react to potential emerging issues by exploring different data sources, e.g., field failure data, customer complaints. However, it is a substantial challenge to explore and digest these data sources due to their large volume coupled with specific technical language in the face of different types of noises. It is also important to construct a single, consistent model to learn technical and non-technical concepts reported in different data sources. In this paper, we propose a deep inductive transfer learning model to automatically extract and classify key technical concepts reported in text fault data from non-technical terms. The newly learned technical concepts provide a crucial semantic backbone to perform downstream engineering tasks, e.g., fault detection and isolation. The proposed model is deployed as a prototype and its performance is validated on different industrial scale data.

关键词： Training Soft sensors Fault detection Transfer learning Semantics Ontologies data models

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Hypergraph-based Modeling of Cognitive dataflow Systems 15

Hypergraph-based Modeling of Cognitive Dataflow Systems

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15th IEEE International Conference on Cognitive Infocommunications, CogInfoCom 2024

作者： Hajdu, Csaba Csapo, Adam B. Department of Informatics Széchenyi István University Győr Hungary Institute of Data Analytics and Information Systems Corvinus Institute for Advanced Studies Corvinus University of Budapest Budapest Hungary

ISBN: (纸本)9798350378245

Cognitive systems have become widespread in various computer-based applications, from assistants to robotic systems. Although such systems are useful even in their current version, there is a growing need to incorporate semantic information. This paper introduces HyMeKo, a framework for modeling information using hypergraphs, which allows for the creation of multiple relationships between information entities through a LALR(1)-based language. The framework’s primary application contexts are in robotics, cyber-physical systems, and intelligent systems. A key innovation of this work is a transformation method between hypergraph semantic descriptions and e-adjacency tensors. An additional practical result from the implementation of the framework is a hypergraph-based dataflow system, enabling the simultaneous description and execution of dataflow processes. The paper includes a minimal example to compare the compactness of the introduced language with the widespread URDF, to describe a minimal, 2-link system, demonstrating its advantages in terms of conciseness and flexibility. © 2024 IEEE.

关键词： Intelligent systems

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New Results on Interval Type-3 Fuzzy Control for Nonlinear Time-Delay Systems Using Convex Relaxation Technique

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IEEE Transactions on Systems, Man, and Cybernetics: Systems 2025年第5期55卷 3630-3641页

作者： Harikaran, B. Harshavarthini, S. Lee, Sangmoon Sakthivel, R. Sathiyaraj, T. School of Advanced Sciences Department of Mathematics Chennai600127 India Kyungpook National University School of Electronic and Electrical Engineering Daegu41566 Korea Republic of Bharathiar University Department of Applied Mathematics Coimbatore641046 India Institute of Actuarial Science and Data Analytics UCSI University Kuala Lumpur56000 Malaysia

In this article, the interval type-3 fuzzy-based state feedback control is proposed for the stabilization problem of interval type-3 fuzzy systems (IT3FSs) subject to time-varying delay. Specifically, to improve the model accuracy and control capabilities, we proposed a nonparallel distributed compensation-based controller approach, be precise, the system and controller adopts the distinct membership functions. Moreover, the stability analysis of IT3FSs in the state space form is studied newly in this article. Besides the primary membership function that exists for interval type-2 fuzzy systems (IT2FSs), the IT3FSs possess the secondary membership function to handle the overall uncertainty which enacts the superiority of the proposed work. Notably, the adequate stability criteria are derived in the form of linear matrix inequality (LMI) using the Lyapunov stability theorem. Additionally, the convex relaxation technique is used to strengthen the design flexibility and achieve the faster convergence rate, which converts an optimization problem with a vector variable to a convex program with a matrix variable, via a lifting technique. A noteworthy aspect is that the application of the convex relaxation technique in the context of IT3FSs is proposed for the first time in literature. Finally, the comparative results between IT2FSs and IT3FSs are shown via two illustrative examples, including the inverted-pendulum model, to underscore the efficacy and practical implementations of the developed control methodology. © 2013 IEEE.

关键词： Membership functions

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DTOR: Decision Tree Outlier Regressor to explain anomalies

arXiv

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arXiv 2024年

作者： Crupi, Riccardo Regoli, Daniele Sabatino, Alessandro Damiano Marano, Immacolata Brinis, Massimiliano Albertazzi, Luca Cirillo, Andrea Cosentini, Andrea Claudio Data Science & Artificial Intelligence Intesa Sanpaolo Italy Audit Data & Advanced Analytics Intesa Sanpaolo Italy

Explaining outliers occurrence and mechanism of their occurrence can be extremely important in a variety of domains. Malfunctions, frauds, threats, in addition to being correctly identified, oftentimes need a valid explanation in order to effectively perform actionable counteracts. The ever more widespread use of sophisticated Machine Learning approach to identify anomalies make such explanations more challenging. We present the Decision Tree Outlier Regressor (DTOR), a technique for producing rule-based explanations for individual data points by estimating anomaly scores generated by an anomaly detection model. This is accomplished by first applying a Decision Tree Regressor, which computes the estimation score, and then extracting the relative path associated with the data point score. Our results demonstrate the robustness of DTOR even in datasets with a large number of features. Additionally, in contrast to other rule-based approaches, the generated rules are consistently satisfied by the points to be explained. Furthermore, our evaluation metrics indicate comparable performance to Anchors in outlier explanation tasks, with reduced execution time. © 2024, CC BY.

关键词： Decision trees

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