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Virtual Reality and 3D User Interfaces Abstracts and Workshops (VRW), IEEE Conference on

作者： Stefania Serafin Ali Adjorlu Rolf Nordahl Federico Fontana Michele Geronazzo Tifanie Bouchara Florent Berthaut Romain Michon Dorte Hammershøj Lorenzo Picinali Department of Architecture Design and Media Technology Aalborg University Copenhagen Denmark Department of Mathematics Computer Science and Physics University of Udine Udine Italy Department of Engineering and Management University of Padova Vicenza Italy LISN CNRS Université Paris-Saclay France CRIStAL CNRS Univ. Lille Lille France INRIA Lyon France Department of Electronic Systems Aalborg University Denmark Dyson School of Design Engineering Imperial College London London UK

ISBN: (数字)9798331514846

ISBN: (纸本)9798331525637

Sonic interaction design is defined as the study and exploitation of sound as one of the principal channels conveying information, meaning, and aesthetic/emotional qualities in interactive contexts. This field lies at the intersection of interaction design, and sound and music *** the virtual reality community, the focus of research on topics related to auditory feedback has been rather limited when compared, for example, to the focus placed on visual feedback or even on haptic feedback. However, in such communities as film production or product sound design it is well known that sound is a powerful way to communicate meaning and emotion to a scene or a *** 2025 is the 8th of a series of workshops, whose main goal is to increase awareness among the virtual reality community of the importance of sonic elements when designing virtual/augmented/mixed reality (XR hereafter) environments. Participants to the workshop will also discuss how research in other related fields such as film sound theory, product sound design, sound and music computing, game sound design, and accessibility can inform designers of XR environments. Moreover, the workshop will feature state-of-the-art research in the field of sound for XR environments.

关键词： Visualization Three-dimensional displays Conferences Spatial audio Music Virtual environments Production Games User interfaces Haptic interfaces

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Discrete Jaya algorithm to solve the police resource deployment problem in emergency traffic accident 10

Discrete Jaya algorithm to solve the police resource deploym...

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10th IEEE Joint International Information technology and Artificial Intelligence Conference, ITAIC 2022

作者： Jing, Zhang Weijie, Ding Zhejiang Police College Department of Computer and Information Security Hangzhou310053 China Big-data and Network Security Research Institute Zhejiang Police College Hangzhou310053 China College of Information Engineering Zhejiang University of Technology Hangzhou310023 China Key Laboratory of Public Security Information Application Based on Big-data Architecture Ministry of Public Security Hangzhou310053 China

ISBN: (数字)9781665422079

ISBN: (纸本)9781665422079

Aiming at the high frequency of urban traffic accidents and the relative shortage of police resources, a multi-objective discrete Jaya algorithm is proposed to solve the problem of police resource deployment in emergency traffic accident handling. The purpose is to make timely response and handling of traffic accidents through the rational allocation of police deployment points in the jurisdiction. Taking the coverage of accident points and the average response time of accidents as the optimization objectives, the discrete Jaya algorithm is used as the global search strategy to approach the Pareto front by constantly approaching the optimal solution and far away from the worst solution, and then the neighborhood search strategy is used to improve the local search ability of the algorithm. Finally, a practical example is given to verify the effectiveness of the proposed method. © 2022 IEEE.

关键词： Law enforcement

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Edge Computing in Smart Cities: Enhancing Real-Time Data Processing

Edge Computing in Smart Cities: Enhancing Real-Time Data Pro...

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Advances in Computation, Communication and Information technology (ICAICCIT), International Conference on

作者： S Rajakumari C Natarajan Vinod N. Alone P Senthilkumar R. Gayathri J Godwin John Department of Mathematics R.M.D. Engineering College Chennai India Department of CSE P. S. R Engineering College Sivakasi Tamilnadu India Computer Engineering Department VPPCOE &VA Sion Mumbai Maharashtra India School of Architecture Koneru Lakshmaiah Education Foundation Vaddeswaram Guntur AP India Department of ECE Rajalakshmi Engineering College Chennai Tamilnadu India Department of Mechanical Engineering Rajalakshmi Institute of Technology Tamil Nadu India

ISBN: (数字)9798331541217

ISBN: (纸本)9798331541224

One of the most crucial issues that smart cities have to keep addressing as they grow is urban mobility improvement. Maximizing the efficiency of transportation, so lowering congestion, and so optimizing traffic flow can help to solve the growing urbanization and increasing vehicle numbers. This research aims to develop and implement a deep learning method based on DenseNet in order to reach the target of raising the effectiveness of urban traffic management. The unique selling proposition that distinguishes this sector from others is the introduction of modern technologies into a sector that has always depended on conventional methods. The main goal of the work was to apply DenseNet architecture to analyze traffic patterns. Considering the two other strategies, the proposed option has a lot of possibilities. From evaluation criteria-which comprised recall, precision, and F1-score, the proposed solution outperformed the approaches regarded to be state-of-the-art.

关键词： Deep learning Smart cities Transportation computer architecture Traffic control Market research Data processing Real-time systems Information and communication technology Edge computing

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Tropes in films: An initial analysis

arXiv

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arXiv 2020年

作者： García-Ortega, Rubén Héctor García-Sánchez, Pablo Merelo-Guervós, Juan Julián Department of Computer Architecture and Technology University of Granada Department of Languages and Computer Systems University of Granada Department of Computer Architecture and Technology University of Granada

TVTropes is a wiki that describes tropes and which ones are used in which artistic work. We are mostly interested in films, so after releasing the TropeScraper Python module that extracts data from this site, in this report we use scraped information to describe statistically how tropes and films are related to each other and how these relations evolve in time. In order to do so, we generated a dataset through the tool TropeScraper in April 2020. We have compared it to the latest snapshot of DB Tropes, a dataset covering the same site and published in July 2016, providing descriptive analysis, studying the fundamental differences and addressing the evolution of the wiki in terms of the number of tropes, the number of films and connections. The results show that the number of tropes and films doubled their value and quadrupled their relations, and films are, at large, better described in terms of tropes. However, while the types of films with the most tropes has not changed significantly in years, the list of most popular tropes has. This outcome can help on shedding some light on how popular tropes evolve, which ones become more popular or fade away, and in general how a set of tropes represents a film and might be a key to its success. The dataset generated, the information extracted, and the summaries provided are useful resources for any research involving films and tropes. They can provide proper context and explanations about the behaviour of models built on top of the dataset, including the generation of new content or its use in machine learning. © 2020, CC BY-SA.

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Drive-Awake: A YOLOv3 Machine Vision Inference Approach of Eyes Closure for Drowsy Driving Detection 3

Drive-Awake: A YOLOv3 Machine Vision Inference Approach of E...

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3rd IEEE International Conference on Artificial Intelligence in Engineering and technology, IICAIET 2021

作者： MacAlisang, Jonel R. Alon, Alvin Sarraga Jardiniano, Moises F. Evangelista, Deanne Cameren P. Castro, Julius C. Tria, Meriam L. Technology Licensing Office-Itso Technological University of the Philippines Manila Philippines Digital Transformation Center Steer Hub Batangas State University Batangas City Philippines Feu Institute of Technology Department of Computer Engineering Manila Philippines College of Engineering and Architecture Bohol Island State University Tagbilaran Bohol Philippines Eulogio Amang Rodriguez Institute of Science and Technology Department of Electronics Engineering Manila Philippines

ISBN: (纸本)9781665428996

Nowadays, road accidents have become a major concern. The drowsiness of drivers owing to overfatigue or tiredness, driving while intoxicated, or driving too quickly is some of the primary causes of this. Drowsy driving contributes to or increases the number of traffic accidents each year. The study presented a technique for detecting driver drowsiness in response to this issue. The sleep states of the drivers in the driving environment were detected using a deep learning approach. To assess if the eyes of particular constant face images of drivers are closed, a convolutional neural network (CNN) model has been developed. The suggested model has a wide range of possible applications, including human-computer interface design, facial expression detection, and determining driver tiredness and drowsiness. The YOLOv3 algorithm, as well as additional tools like Pascal VOC and LabelImg, were used to build this approach, which collects and trains a driver dataset that feels drowsy. The study's total detection accuracy was 100%, with detection per frame accuracy ranging from 49% to 89%. © 2021 IEEE.

关键词： Object detection

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Adaptable Invisibility Management Using Kirigami-Inspired Transformable Metamaterials

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Research 2021年第1期2021卷 1034-1044页

作者： He-Xiu Xu Mingzhao Wang Guangwei Hu Shaojie Wang Yanzhao Wang Chaohui Wang Yixuan Zeng Jiafang Li Shuang Zhang Wei Huang Air and Missile Defense College Air Force Engineering UniversityXi’an 710051China Institute of Flexible Electronics Northwestern Polytechnical UniversityXi’an 710072China Department of Electrical and Computer Engineering National University of SingaporeSingaporeSingapore 117583 Centre for Quantum Physics Key Laboratory of Advanced Optoelectronic Quantum Architecture and Measurement(MOE)Beijing 100081China School of Physics Beijing Institute of TechnologyBeijing 100081China Department of Physics University of Hong KongHong KongChina Department of Electronic&Electrical Engineering University of Hong KongHong KongChina

Many real-world applications,including adaptive radar scanning and smart stealth,require reconfigurable multifunctional devices to simultaneously manipulate multiple degrees of freedom of electromagnetic(EM)waves in an on-demand ***,kirigami technique,affording versatile and unconventional structural transformation,has been introduced to endow metamaterials with the capability of controlling EM waves in a reconfigurable ***,we report for a kirigami-inspired sparse meta-architecture,with structural density of 1.5%in terms of the occupation space,for adaptive invisibility based on independent operations of frequency,bandwidth,and *** on the general principle of dipolar management via structural reconstruction of kirigami-inspired meta-architectures,we demonstrate reconfigurable invisibility management with abundant EM functions and a wide tuning range using three enantiomers(A,B,and C)of different geometries characterized by the folding angleβ.Our strategy circumvents issues of limited abilities,narrow tuning range,extreme condition,and high cost raised by available reconfigurable metamaterials,providing a new avenue toward multifunctional smart devices.

关键词： tuning visibility smart

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Deep learning based Identification of Solid Waste Management in Smart Cities through Garbage Separation and Monitoring 5

Deep learning based Identification of Solid Waste Management...

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5th International Conference on Inventive Research in Computing Applications, ICIRCA 2023

作者： George, Abin Mankar, Sham H. Suryanarayana, N.V.S. Gupta, Manish Sathish, R. Priya, A. Knowledge and Technology Management Division Council of Scientific & Industrial Research National Aerospace Laboratories Karnataka Bangaluru India Pimpri Chinchwad College of Engineering and Research Department of Mechanical Engineering Maharashtra Pune India Central Tribal University of Andhra Pradesh Administrative Officer Andhra Pradesh Vizianagaram India Lovely Professional University Division of Research and Development Punjab Phagwara India Shri Nehru Maha Vidayala College of Arts and Science Department of Computer Science Tamil Nadu Coimbatore India School of Architecture Koneru Lakshmaiah Educational Foundation Andhra Pradesh Gundur India

ISBN: (纸本)9798350321425

The solid waste management is the process of proper decomposition of waste materials within a period of time. This includes the collection of garbage's and then proceeded through certain measures for decomposition. There are various methods adopted in the garbage separation process. This includes the artificial intelligence techniques for the estimation and determination of the solid waste through automatic detection and separation of the garbage waste using control and sensing units. They are integrated with the internet of things to enable the two way communication system. This helps to visualize the functioning of the system adopting the digital platform. The proposed system is implemented through the smart dust bin held in every household that automatically senses the non-biodegradable and biodegradable waste materials. The classification of the waste materials are identified through the image processing techniques. © 2023 IEEE.

关键词： Genetic algorithms

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Constrained Optimization with Decision-Dependent Distributions

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IEEE Transactions on Automatic Control 2025年

作者： Wang, Zifan Liu, Changxin Parisini, Thomas Zavlanos, Michael M. Johansson, Karl H. KTH Royal Institute of Technology Division of Decision and Control Systems School of Electrical Engineering and Computer Science Sweden Digital Futures StockholmSE-10044 Sweden East China University of Science and Technology Key Laboratory of Smart Manufacturing in Energy Chemical Process Ministry of Education Shanghai200237 China Imperial College London Department of Electrical and Electronic Engineering LondonSW7 2AZ United Kingdom Aalborg University Department of Electronic Systems Denmark University of Trieste Department of Engineering and Architecture Italy Duke University Department of Mechanical Engineering and Materials Science DurhamNC United States

In this paper we deal with stochastic optimization problems where the data distributions change in response to the decision variables. Traditionally, the study of optimization problems with decision-dependent distributions has assumed either the absence of constraints or fixed constraints. This work considers a more general setting where the constraints can also dynamically adjust in response to changes in the decision variables. Specifically, we consider linear constraints and analyze the effect of decision-dependent distributions in both the objective function and constraints. Firstly, we establish a sufficient condition for the existence of a constrained equilibrium point, at which the distributions remain invariant under retraining. Moreover, we propose and analyze two algorithms: repeated constrained optimization and repeated dual ascent. For each algorithm, we provide sufficient conditions for convergence to the constrained equilibrium point. Furthermore, we explore the relationship between the equilibrium point and the optimal point for the constrained decision-dependent optimization problem. Notably, our results encompass previous findings as special cases when the constraints remain fixed. To show the effectiveness of our theoretical analysis, we provide numerical experiments on both a market problem and a dynamic pricing problem for parking based on real-world data. © 1963-2012 IEEE.

关键词： Optimization algorithms

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The Importance of Being Earnest: Multiple Heterogeneous Container Loading with a Simple Genetic Algorithm 28th

The Importance of Being Earnest: Multiple Heterogeneous Con...

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28th European Conference on Applications of Evolutionary Computation, EvoApplications 2025, held as part of EvoStar 2025

作者： Rusin, Francesco Fiala, Jan Sanker, Julian Bhattarai, Suyesh Ekárt, Anikó Department of Engineering and Architecture University of Trieste Trieste Italy Institute of Automation and Computer Science Brno University of Technology Brno Czech Republic Yale College Yale University New Haven United States Mechatherm International Limited Cradley Heath United Kingdom Aston Centre for Artificial Intelligence Research and Application Aston University Birmingham United Kingdom

ISBN: (纸本)9783031900617

In this study we address the complex practical problem of multiple heterogeneous container loading with a simple genetic algorithm. We demonstrate that with a well-chosen representation including a heuristic and a suitable fitness function the other aspects of the genetic algorithm do not need extensive work for good results. Following systematic study of our method on synthetically generated data, we visually showcase the solution for a company-based problem instance. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Genetic algorithms

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Data Fusion in Neuromarketing: Multimodal Analysis of Biosignals, Lifecycle Stages, Current Advances, Datasets, Trends, and Challenges

SSRN

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SSRN 2023年

作者： Pérez, Mario Quiles Beltrán, Enrique Tomás Martínez Bernal, Sergio López Prat, Eduardo Horna Del Campo, Luis Montesano Maimó, Lorenzo Fernández Celdrán, Alberto Huertas Department of Information and Communications Engineering University of Murcia Murcia30100 Spain Bit&Brain Technologies S.L Zaragoza50006 Spain Department of Computer Architecture and Technology University of Murcia Murcia30100 Spain Communication Systems Group CSG Department of Informatics IfI University of Zurich UZH ZürichCH—8050 Switzerland

The primary goal of any company is to increase its profits by improving both the quality of its products and how they are advertised. In this context, neuromarketing seeks to enhance the promotion of products and generate a greater acceptance on potential buyers. Traditionally, neuromarketing studies have relied on a single biosignal to obtain feedback from presented stimuli. However, thanks to new devices and technological advances studying this area of knowledge, recent trends indicate a shift towards the fusion of diverse biosignals. An example is the usage of electroencephalography for understanding the impact of an advertisement at the neural level and visual tracking to identify the stimuli that induce such impacts. This emerging pattern determines which biosignals to employ for achieving specific neuromarketing objectives. Furthermore, the fusion of data from multiple sources demands advanced processing methodologies. Despite these complexities, there is a lack of literature that adequately collates and organizes the various data sources and the applied processing techniques for the research objectives pursued. To address these challenges, the current paper conducts a comprehensive analysis of the objectives, biosignals, and data processing techniques employed in neuromarketing research. This study provides both the technical definition and a graphical distribution of the elements under revision. Additionally, it presents a categorization based on research objectives and provides an overview of the combinatory methodologies employed. After this, the paper examines primary public datasets designed for neuromarketing research together with others whose main purpose is not neuromarketing, but can be used for this matter. Ultimately, this work provides a historical perspective on the evolution of techniques across various phases over recent years and enumerates key lessons learned. © 2023, The Authors. All rights reserved.

关键词： Life cycle

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