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arXiv 2024年

作者： Wu, Keshu Li, Pei Cheng, Yang Parker, Steven T. Ran, Bin Noyce, David A. Ye, Xinyue Department of Civil and Environmental Engineering The University of Wisconsin-Madison MadisonWI53706 United States Department of Landscape Architecture and Urban Planning The Zachry Department of Civil and Environmental Engineering Texas A&M University College StationTX77840 United States Center for Geospatial Sciences Applications and Technology The Department of Landscape Architecture and Urban Planning Department of Computer Science and Engineering Texas A&M University College StationTX77840 United States

Transportation Cyber-Physical Systems (T-CPS) enhance safety and mobility by integrating cyber and physical transportation systems. A key component of T-CPS is the Digital Twin (DT), a virtual representation that enables simulation, analysis, and optimization through real-time data exchange and communication. Although existing studies have explored DTs for vehicles, communications, pedestrians, and traffic, real-world validations and implementations of DTs that encompass infrastructure, vehicles, signals, communications, and more remain limited due to several challenges. These include accessing real-world connected infrastructure, integrating heterogeneous, multi-sourced data, ensuring real-time data processing, and synchronizing the digital and physical systems. To address these challenges, this study develops a traffic DT based on a real-world connected vehicle corridor. Leveraging the Cellular Vehicle-to-Everything (C-V2X) infrastructure in the corridor, along with communication, computing, and simulation technologies, the proposed DT accurately replicates physical vehicle behaviors, signal timing, communications, and traffic patterns within the virtual environment. Building upon the previous data pipeline, the digital system ensures robust synchronization with the physical environment. Moreover, the DT’s scalable and redundant architecture enhances data integrity, making it capable of supporting future large-scale C-V2X deployments. Furthermore, its ability to provide feedback to the physical system is demonstrated through applications such as signal timing adjustments, vehicle advisory messages, and incident notifications. The proposed DT is a vital tool in T-CPS, enabling real-time traffic monitoring, prediction, and optimization to enhance the reliability and safety of transportation systems. © 2024, CC BY.

关键词： Vehicle to infrastructure

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SSI meets Metaverse for Industry 4.0 and Beyond

TechRxiv

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TechRxiv 2022年

作者： Cali, Umit Ferdous, Md Sadek Karaarslan, Enis Gourisetti, Nikhil Gupta Mylrea, Michael Department of Electric Power Engineering Norwegian University of Science and Technology Trondheim Norway Department of Computer Science and Engineering BRAC University Dhaka Bangladesh Department of Computer Engineering Muğla Sıtkı Koçman University Muğla Turkey Department of Security Architecture National Resilience La Jolla CA United States

As the global industrial complex gears toward fulfilling the tenets of Industry 4.0 and beyond, technologies such as distributed ledger technologies, digital twins, and artificial intelligence become pivotal enablers. In the last decade, metaverse as a concept and technology found its place among crucial enablers for technology and digital advancement across several engineering domains. Metaverse has the potential to combine the elements from distributed computing platforms, the digital evolution of physical systems, and advanced learning systems to unearth a fully digitized world of comparative properties of the real world. We should ensure the privacy, integrity, and confidentiality of personal data. These requirements will lead to proper identity management in the metaverse. Given the complex nature of the metaverse, traditional centralized systems may not offer a viable identity management solution. Therefore, this study explores a decentralized identity management system called the Self-sovereign Identity (SSI) as a logical alternative to traditional centralized identity management systems. The proposed holistic framework aims to ignite new ideas and discussions related to the combined deployment of DLT, SSI, and metaverse to inspire new implementation areas within the Industry 4.0 environment. The paper also discusses various opportunities, enablers, technical & privacy aspects, legislation requirements, and other barriers related to SSI implementation. © 2022, CC BY.

关键词： Industry 4.0

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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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SSI meets Metaverse for Industry 4.0 and Beyond

SSI meets Metaverse for Industry 4.0 and Beyond

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Global Emerging technology Blockchain Forum: Blockchain & Beyond (iGETblockchain), IEEE

作者： Umit Cali Md Sadek Ferdous Enis Karaarslan Sri Nikhil Gupta Gourisetti Michael Mylrea Department of Electric Power Engineering Norwegian University of Science and Technology Trondheim Norway Department of Computer Science and Engineering BRAC University Dhaka Bangladesh Department of Computer Engineering Muğla Sıtkı Koçman University Muğla Türkiye Department of Security Architecture National Resilience La Jolla CA USA

As the global industrial complex gears toward fulfilling the tenets of Industry 4.0 and beyond, technologies such as distributed ledger technologies, digital twins, and artificial intelligence become pivotal enablers. In the last decade, metaverse as a concept and technology found its place among crucial enablers for technology and digital advancement across several engineering domains. Metaverse has the potential to combine the elements from distributed computing platforms, the digital evolution of physical systems, and advanced learning systems to unearth a fully digitized world of comparative properties of the real world. We should ensure the privacy, integrity, and confidentiality of personal data. These requirements will lead to proper identity management in the metaverse. Given the complex nature of the metaverse, traditional centralized systems may not offer a viable identity management solution. Therefore, this study explores a decentralized identity management system called the Self-sovereign Identity (SSI) as a logical alternative to traditional centralized identity management systems. The proposed holistic framework aims to ignite new ideas and discussions related to the combined deployment of DLT (Distributed Ledger technology), SSI, and metaverse to inspire new implementation areas within the Industry 4.0 environment. The paper also discusses various opportunities, enablers, technical & privacy aspects, legislation requirements, and other barriers related to SSI implementation.

关键词： Privacy Metaverse Distributed ledger Shape Supply chains Transportation Market research

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Meta-Learning Based Infrared Ship Object Detection Model for Generalization to Unknown Domains

SSRN

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SSRN 2023年

作者： Feng, Hui Tang, Wei Xu, Haixiang Jiang, Chengxin Ge, Shuzhi Sam He, Jianhua Key Laboratory of High-Performance Ship Technology of Ministry of Education Wuhan University of Technology Wuhan430063 China School of Naval Architecture Ocean and Energy Power Engineering Wuhan University of Technology Wuhan430063 China Department of Electrical and Computer Engineering National University of Singapore Singapore117576 Singapore School of Computer Science and Electronic Engineering University of Essex CO4 3SQ United Kingdom

Infrared images exhibit considerable variations in probability distributions, stemming from the utilization of distinct infrared sensors and the influence of diverse environmental conditions. The variations pose great challenges for deep learning models to detect ship objects and adapt to unseen maritime environments. To address the domain shift problem, we propose an end-to-end infrared ship object detection model based on meta-learning neural network to improve domain adaptation for target domain where data is not available at training phase. Different from existing domain generalization methods, the novelty of our model lies in the effective exploition of meta-learning and domain adaptation, ensuring that the extracted domain-independent features are meaningful and domain-invariant at the semantic level. Firstly, a double gradient-based meta-learning algorithm is designed to solve the common optimal descent direction between different domains through two gradient updates in the inner and outer loops. The algorithm enables extraction of domain-invariant features from the pseudo-source and pseudo-target domain data. Secondly, a domain discriminator with dynamic-weighted gradient reversal layer (DWGRL) is designed to accurately classify domain-invariant features and provide additional global supervision information. Finally, a multi-scale feature aggregation method is proposed to improve the extraction of multi-scale domain-invariant features. It can effectively fuse local features at different scales and global features of targets. Extensive experimental results conducted in real nighttime water surface scenes demonstrate that the proposed model achieves very high detection accuracy on target domain data, even no target domain data was used during the training phase. Compared to the existing methods, our method not only improves the detection accuracy of infrared ships by 18%, but also exhibits the smallest standard deviation with a value of 0.93, indicating its su

关键词： Object detection

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Overview of the Tenth Dialog System technology Challenge: DSTC10

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IEEE/ACM Transactions on Audio Speech and Language Processing 2024年 32卷 765-778页

作者： Yoshino, Koichiro Chen, Yun-Nung Crook, Paul Kottur, Satwik Li, Jinchao Hedayatnia, Behnam Moon, Seungwhan Fei, Zhengcong Li, Zekang Zhang, Jinchao Feng, Yang Zhou, Jie Kim, Seokhwan Liu, Yang Jin, Di Papangelis, Alexandros Gopalakrishnan, Karthik Hakkani-Tur, Dilek Damavandi, Babak Geramifard, Alborz Hori, Chiori Shah, Ankit Zhang, Chen Li, Haizhou Sedoc, Joao D'haro, Luis F. Banchs, Rafael Rudnicky, Alexander Guardian Robot Project R-IH RIKEN 2-2-2 Hikaridai Seika Shoraku619-0288 Japan Information Science Nara Institute of Science and Technology Ikoma630-0101 Japan Computer Science and Information Engineering National Taiwan University Taipei10617 Taiwan Inc. Palo AltoCA95054 United States Alexa AI *** Inc. SunnyvaleCA94089 United States Meta Seattle RedmondWA98052 United States Institute of Computing Technology Chinese Academy of Sciences Beijing100190 China Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences Beijing100190 China Tencent AI Lab Beijing Beijing China Kexueyuan South Road Zhongguancun Beijing100190 China Beijing 100190 China Alexa AI *** Inc. SunnyvaleCA United States 1120 Enterprise way Sunnyvale94089 United States *** Inc. SeattleWA United States Menlo Park CA United States Audio and Speech Group Mitsubishi Electric Research Laboratories CambridgeMA02139-1955 United States Carnegie Mellon University Department of Language and Information Technologies or just Carnegie Mellon University Pittsburgh United States National University of Singapore Singapore Singapore Department of Electrical and Computer Engineering National University of Singapore Singapore Singapore Shenzhen Research Institute of Big Data School of Data Science Chinese University of Hong Kong Shenzhen518172 China New York University New YorkNY United States ETSI de Telecomunicacion - Speech Technology and Machine Learning Group Universidad Politecnica de Madrid Ciudad Universitaria Madrid28040 Spain Nanyang Technological University Singapore Singapore Carnegie Mellon University PittsburghPA United States

This article introduces the Tenth Dialog System technology Challenge (DSTC-10). This edition of the DSTC focuses on applying end-to-end dialog technologies for five distinct tasks in dialog systems, namely 1. Incorporation of Meme images into open domain dialogs, 2. Knowledge-grounded Task-oriented Dialogue Modeling on Spoken Conversations, 3. Situated Interactive Multimodal dialogs, 4. Reasoning for Audio Visual Scene-Aware Dialog, and 5. Automatic Evaluation and Moderation of Open-domainDialogue Systems. This article describes the task definition, provided datasets, baselines, and evaluation setup for each track. We also summarize the results of the submitted systems to highlight the general trends of the state-of-the-art technologies for the tasks. © 2023 The Authors.

关键词： Job analysis

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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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Gender Prediction from Direct Pelvic Radiographs Using Efficientnet Deep Learning Model

SSRN

引用

SSRN 2024年

作者： Secgin, Yusuf Toy, Seyma Çakmak, Muhammet Oner, Zulal Ciftci, Rukiye Oner, Serkan Karabük University Faculty of Medicine Department of Anatomy Karabük Turkey Sinop University Faculty of Engineering and Architecture Department of Computer Engineering Sinop Turkey İzmir Bakırçay University Faculty of Medicine Department of Anatomy İzmir Turkey Gaziantep Islamic University of Science and Technology Department of Anatomy Gaziantep Turkey İzmir Bakırçay University Faculty of Medicine Department of Radiology İzmir Turkey

Objectives: EfficientNet is an up-to-date deep learning (DL) architecture and an important computer-based algorithm for forensic and basic medical sciences. The aim of this study is to perform highly accurate and precise gender estimation with images obtained from direct pelvic radiographs (X-Ray) using the EfficientNet deep learning *** and Methods: The study was performed using pelvis X-Ray images of 423 individuals aged 18-65 years. For the reliability of the DL architecture, data augmentation was applied to the images and the data set was increased to 1400. EfficientNet V2 B0 architecture was applied to the increased data set. The performance of the architecture was also compared using NASNet Mobile and ResNet152 rooted ***: As a result of the study, a gender prediction rate of 99.29% was obtained with the EfficientNet architecture, 97.86% with the NASNet Mobile architecture and 95.71% with the ResNet152 ***: As a result of the study, EfficientNet V2 B0, NASNet Mobile and ResNet152 DL architectures showed high accuracy and reliability in terms of gender estimation. In this respect, we believe that this study will guide forensic and basic medical sciences. © 2024, The Authors. All rights reserved.

关键词： X ray radiography

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Manufacturing A Low-Cost Telegram and Optical Character Recognition-Based Indoor Air Quality Monitoring Data Logger

Manufacturing A Low-Cost Telegram and Optical Character Reco...

引用

International Conference on Information Management and technology (ICIMTech)

作者： Andi Pramono Satrio Arif Budiman Muchammad Farchan Andi Baso Mappaturi Interior Design Department School of Design Bina Nusantara University Jakarta Indonesia Information System Computer Science Faculty Brawijaya University Malang Indonesia Department of Electrical Engineering Faculty of Intelligent Electrical and Informatics Technology Institut Teknologi Sepuluh Nopember Surabaya Indonesia Architecture Department Faculty of Science and Technology Islamic State University of Maulana Malik Ibrahim Malang Indonesia

Urban air is frequently contaminated with CO, CO2, VOC, HCHO, PM 2.5, and PM 10. Rural regions are at a lower risk than those near roads and industrial areas that produce emissions. Air pollutants negatively affect its inhabitants' health, particularly the respiratory system. Most people will spend more time indoors, requiring a method for monitoring indoor air quality (IAQ). Urban communities need IAQ monitoring instruments as an early warning system for their health. This research seeks to produce inexpensive IAQ that can be utilized by all levels of society, particularly urban communities. This research utilizes a qualitative, design-thinking-based methodology. The research diverged from Empatize, which asserts that urban communities require a method for determining the local air quality. Moreover, it is determined at the define stage that IAQ monitoring, which includes a data log feature, is still comparatively expensive, so a solution is developed at the ideate stage. Creating a prototype is the next step in realizing the specified solution. In this investigation, they decided to use IAQ monitoring, which is relatively inexpensive but lacks log data storage. The author uses the ESP32-cam microcontroller to capture the screen display device, and the resulting image is sent to a telegram and processed with optical character recognition (OCR) to generate a data log. The results of prototype testing are utilized for prototype development.

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Investigation of Circular Patch Antenna for Wi-Fi and Bluetooth Applications

Investigation of Circular Patch Antenna for Wi-Fi and Blueto...

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Advancement in Electronics & Communication Engineering (AECE), International Conference on

作者： Maryam Ghassan Majeed Haitham Bashar Qasim Shakhlokhon Kosimova Hussein Alaa Diame Alaa M. Lafta Haider Alchilibi Computer Engineer Department Al-Kunooze University College Basra Iraq Forensic sciences department Al-Esraa University College Baghdad Iraq Department of Architecture Fergana Polytechnic Institute Fergana Uzbekistan National University of Science and Technology Dhi Qar Iraq Medical Laboratory Techniques Department Al-Farahidi University Baghdad Iraq

The purpose of this paper is to examine and contrast the Novel Circular Patch Antenna employing FR4 and RT Droid (CPA). Resonant frequency of 2.5 GHz in a static medium. To create the antenna, we use the HFSS and two different sample sets. Ten samples are taken from each antenna at 80% G-Power. Assume that the members of Group 1 are all CPAs that use the FR4 substrate. The Novel circular patch antenna (CPA) on RT roger's substrate is in the second group under consideration. This antenna operates at 2.5 GHz to measure reflectance at both ends. A VSWR of 2.1786 dB was measured at 2.4 GHz for a circular CPA designed for RT rogers, while the measured value for a CPA with FR4 was 0.7088 dB. The significance level in SPSS was 0.038 (p 0.05). The findings of this study show that RT rogers is approximately as effective as the FR4 substrate.

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