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1st International Conference on Cyber Physical Systems, Power Electronics and Electric Vehicles, ICPEEV 2023

作者： Puri, Vikram Solanki, Vijender Kumar Kataria, Aman Long, Cu Kim Duy Tan University Center of Visualization and Simulation Da Nang Viet Nam Cmr Institute of Technology Dept. of Computer Science and Engineering TS Hyderabad India Amity University Amity Institute of Defence Technology Uttar Pradesh India Information Technology Center Hanoi Viet Nam

ISBN: (纸本)9798350323566

The development and growth of the shared economy in the smart cities are significantly influenced by technology. An online community-based ecosystem that enables peer-to-peer trade between buyers and sellers as well as share- and rental-based access to goods and services. Lack of trust and transparency is the main problem in the shared economy system. A blockchain-enabled architecture is created for the shared economy ecosystem to address this problem. In this study, product registration and product services policies are implemented using smart contracts. This technology aids in distinguishing between genuine and counterfeit goods while also giving consumers access to the product's metadata via QR codes. An experimental testbed that makes use of the polygon network is taken into consideration in order to validate the suggested framework. © 2023 IEEE.

关键词： Smart city

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Optimal scheduling with energy constraints

Optimal scheduling with energy constraints

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2008 AIChE Annual Meeting, AIChE 100

作者： Castro, Pedro Harjunkoski, Iiro Grossmann, Ignacio E. Department of Process Modeling and Simulation INETI Lisbon Portugal Corporate Research ABB Ladenburg Germany Dept. of Chemical Engineering Center for Advanced Process Decision-making Carnegie Mellon University 5000 Forbes Avenue Pittsburgh PA 15213 United States

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Evolutionary Interest Representation Network for Click-Through Rate Prediction

Evolutionary Interest Representation Network for Click-Throu...

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2023 IEEE International Conference on Web Services, ICWS 2023

作者： Zhou, Renjie Jin, Zhenming Wan, Jian Zhang, Jilin Guo, Xingyu Liu, Qiang Hangzhou Dianzi University Key Laboratory of Complex Systems Modeling and Simulation of the Ministry of Education School of Computer Science and Technology Hangzhou China Hangzhou Dianzi University Key Laboratory of Complex Systems Modeling and Simulation of the Ministry of Education Itmo Joint Institute Hangzhou China Zhejiang University of Science and Technology School of Information and Electronic Engineering Hangzhou China Zhejiang Police College Dept. of Computer and Information Technology Hangzhou China

ISBN: (纸本)9798350304855

The rapid development of the Internet has revo-lutionized our lives, providing us with an array of convenient services. However, this revolution has also led to the problem of data overload. Personalized recommendation services have been widely recognized as an effective solution to this problem by both the industrial and academic communities. Accurate prediction of click-through rate (CTR) is a critical task in personalized recommendation systems since it can improve the user's shopping experience, ultimately increasing revenue for the platform. To achieve accurate CTR prediction, it is crucial to capture user interests. While several methods for interest modeling exist, challenges related to user interest evolution and user behavior noise need further attention. This paper proposes a novel CTR prediction model named the Evolutionary Interest Representation Network (EIRN), which learns the evolving interest representation of users from their behaviors, profiles, and environmental attributes. In the model, we introduce an advertisement correlation graph decomposition layer and a noise filter layer to enhance and purify the user behavior representation. An interest extraction layer is designed to capture sequential correlations and common characteristics between user behaviors, representing their interests. Additionally, as user interests evolve over time and their importance changes, an attention-based interest evolution layer is designed to track the evolution of user interests. Our proposed method is validated using four public datasets and an industrial dataset, showing its superiority over existing CTR prediction methods. © 2023 IEEE.

关键词： Forecasting

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A Smart Microgrid Approach for Distributed Network Combined with Power Line Fault Location Detection

A Smart Microgrid Approach for Distributed Network Combined ...

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2021 IEEE International Conference on Automatic Control and Intelligent Systems, I2CACIS 2021

作者： Khushi, Farha Motakabber, S.M.A. Bhattacharjee, Amit Zahirul Alam, A.H.A. Wong Azman, Amelia Hussain, Fayaz Kulliyyah of Engineering IIUM Dept. of Electronic and Computer Engineering Gombak Malaysia The City University Of New York Department Of Electrical And Computer Engineering New YorkNY United States Ton Duc Thang University Modeling Evolutionary Algorithms Simulation and Artificial Intelligence Faculty of Electrical Electronics Engineering Ho Chi Minh City Viet Nam

ISBN: (纸本)9781665403436

For every researcher, uncertainties connected to the Smart Grid and Distribution Network are a common element. Thousands of sources are part of the renewable energy system and they are situated at varying distances. In due course, certain sources may be inefficient, or a natural disaster can destroy the source causing power supply failures or require routine maintenance to improve service. Some of these defects grow slowly and some have a strong impact. The systems, however, contain safety components to remove the problem, but impact the generation of electricity and conduct intelligent grid errors. An intelligent microgrid should feature an intelligent fault location detection and fault removal device to avoid unwanted loads and insecurities. This research shaped a smart grid system, together with a defective technique to identify uncertainty efficiently. The originality of this research is to model an SMG based on an isolated small area's SGC mechanism in conjunction with a defective detecting system to manage uncertainties in an efficient way. The FLD technique is focused upon wavelet trigger signal and mathematical morphology method. In this approach, the wavelet activator signal created by the equivalent current or voltage for a short period of time is simulated to go to both terminals to determine that the fault takes place in the short branch using the mathematical morphological technique. The SMG modeled system is separated into a few branches for the FLD system. A smart technique is presented via mixed human machine interface (HMI) for SMG performance and FLD monitoring. The integrated process of the SMG system modeling in the MATLAB performance validation simulation platform. © 2021 IEEE.

关键词： Mathematical morphology

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DLT Based Smart Medical Ecosystem

DLT Based Smart Medical Ecosystem

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2023 IEEE International Conference on Network, Multimedia and Information Technology, NMITCON 2023

作者： Puri, Vikram Kataria, Aman Rani, Sita Pareek, Piyush Kumar Duy Tan University Center of Visualization and Simulation Da Nang Viet Nam Amity Institute of Defence Technology Amity University Uttar Pradesh Noida India Guru Nanak Dev Engineering College Department of Computer Science and Engineering Ludhiana India Nitte Meenakshi Institute of Technology Dept. of Artificial Intelligence and Machine Learning Bengaluru India

ISBN: (纸本)9798350300826

The healthcare system has become more reliant on the data collection capabilities of fast evolving IoT devices. Patient healthcare records (PHR) now contain additional information as a result. However, securing identities and guaranteeing data security have emerged as critical challenges in the healthcare system. When it comes to regulating PHR, many of the centralized and decentralized methods now in use struggle difficulties such as single point of failure, high transaction fees, slow throughput, and excessive latency. To address these concerns, a distributed ledger technology (DLT)-based framework named IOTA rather than a blockchain-based platform such as Ethereum or Polygon is proposed. The proposed framework considered the example of a hospital with several patients on the same and various floors. Furthermore, the suggested approach employs a real-time experimental setup for calculating the time and power consumption of the devices. © 2023 IEEE.

关键词： Distributed ledger

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Scalable atomistic simulation algorithms for materials research

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Scientific Programming 2002年第4期10卷 263-270页

作者： Nakano, Aiichiro Kalia, Rajiv K. Vashishta, Priya Campbell, Timothy J. Ogata, Shuji Shimojo, Fuyuki Saini, Subhash Department of Computer Science Dept. of Mat. Sci. and Engineering University of Southern California Los Angeles CA 90089 United States Concurrent Computing Lab. for MS Biol. Comp. and Visualization Center Louisiana State University Baton Rouge LA 70803 United States Department of Applied Sciences Yamaguchi University Ube 755-8611 Japan Faculty of Integrated Arts and Sci. Hiroshima University Higashi-Hiroshima 739-0046 Japan IT Modeling and Simulation NASA Ames Research Center Moffett Field CA 94035-1000 United States

A suite of scalable atomistic simulation programs has been developed for materials research based on space-time multiresolution algorithms. Design and analysis of parallel algorithms are presented for molecular dynamics (MD) simulations and quantum-mechanical (QM) calculations based on the density functional theory. Performance tests have been carried out on 1,088-processor Cray T3E and 1,280-processor IBM SP3 computers. The linear-scaling algorithms have enabled 6.44-billion-atom MD and 111,000-atom QM calculations on 1,024 SP3 processors with parallel efficiency well over 90%. The production-quality programs also feature wavelet-based computational-space decomposition for adaptive load balancing, spacefilling-curve-based adaptive data compression with user-defined error bound for scalable I/O, and octree-based fast visibility culling for immersive and interactive visualization of massive simulation data.

关键词： Parallel algorithms

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Evaluating kinect V1 and V2 for chest wall surface scanning and assessment 8

Evaluating kinect V1 and V2 for chest wall surface scanning ...

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8th International Workshop on Innovative simulation for Health Care, IWISH 2019

作者： Kidane, Nahom Obeid, Mohammad F. Hall, Cierra Sakioti, Ntiana Kelly, Robert E. McKenzie, Frederic D. Dept. of Computational Modeling and Simulation Engineering Old Dominion University Norfolk United States Division of Applied Technology Shenandoah University Winchester United States Pediatric Surgery Children's Hospital King's Daughters and Eastern Virginia Medical School Norfolk United States

ISBN: (纸本)9788885741362

Optical scanning has proven to be advantageous to objectively assess the severity of chest wall deformities and the effectiveness of its treatment. By potentially eliminating the need for computed tomography (CT) scanning and superseding manual measurements that are subject to errors, a system that utilizes optical scanning presents great value to patients and practitioners. This work aims to investigate and evaluate the performance of two off-the-shelf optical scanning sensors in the context of their utility and accuracy to measure the severity of chest wall deformities. An in-vitro experiment and a human study are conducted utilizing both sensors to collect data and report the findings. © Innovative simulation for Health Care, IWISH *** Rights Reserved.

关键词： Scanning

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Exploring Challenges in Deep Learning of Single-Station Ground Motion Records

SSRN

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SSRN 2024年

作者： Çaglar, Ümit Mert Yilmaz, Baris Türkmen, Melek Tileylioglu, Salih Akagündüz, Erdem Dept. of Modeling and Simulation Graduate School of Informatics Middle East Technical University Ankara Turkey Dept. of Civil Engineering Kadir Has University Istanbul Turkey

Contemporary deep learning models have demonstrated promising results across various applications within seismology and earthquake engineering. These models rely primarily on utilizing ground motion records for tasks such as earthquake event classification, localization, earthquake early warning systems, and structural health monitoring. However, the extent to which these models effectively learn from these complex time-series signals has not been thoroughly *** this study, our objective is to evaluate the degree to which auxiliary information, such as seismic phase arrival times or seismic station distribution within a network, dominates the process of deep learning from ground motion records, potentially hindering its *** perform a hyperparameter search on two deep learning models to assess their effectiveness in deep learning from ground motion records while also examining the impact of auxiliary information on model performance. Experimental results reveal a strong reliance on the highly correlated Primary (P) and Secondary (S) phase arrival *** observations highlight a potential gap in the field, indicating an absence of robust methodologies for deep learning of single-station ground motion recordings independent of any auxiliary information. © 2024, The Authors. All rights reserved.

关键词： Structural health monitoring

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Exploring Challenges in Deep Learning of Single-Station Ground Motion Records

arXiv

引用

arXiv 2024年

作者： Çaǧlar, Ümit Mert Yilmaz, Baris Türkmen, Melek Akagündüz, Erdem Tileylioglu, Salih Dept. of Modeling and Simulation Graduate School of Informatics Middle East Technical University Ankara Turkey Dept. of Civil Engineering Kadir Has University Istanbul Turkey

Contemporary deep learning models have demonstrated promising results across various applications within seismology and earthquake engineering. These models rely primarily on utilizing ground motion records for tasks such as earthquake event classification, localization, earthquake early warning systems, and structural health monitoring. However, the extent to which these models effectively learn from these complex time-series signals has not been thoroughly analyzed. In this study, our objective is to evaluate the degree to which auxiliary information, such as seismic phase arrival times or seismic station distribution within a network, dominates the process of deep learning from ground motion records, potentially hindering its effectiveness. We perform a hyperparameter search on two deep learning models to assess their effectiveness in deep learning from ground motion records while also examining the impact of auxiliary information on model performance. Experimental results reveal a strong reliance on the highly correlated P and S phase arrival information. Our observations highlight a potential gap in the field, indicating an absence of robust methodologies for deep learning of single-station ground motion recordings independent of any auxiliary information. © 2024, CC BY.

关键词： Structural health monitoring

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Parachute suspension line drag analysis

Parachute suspension line drag analysis

引用

作者： Bergeron, K. Curlett, T. Ecklebe, D. McClure, K. Pitman, B. Johari, H. Department of Aeronautics USAF Academy CO 80840 United States California State University Northridge CA 91330 United States Modeling and Simulation Research Center Dept. of Aeronautics 2410 Fairchild Dr. United States Dept. of Aeronautics 2410 Fairchild Dr. United States Mechanical Engineering Dept. 18111 Nordoff Street United States

ISBN: (纸本)9781563479724

A team of researchers experimentally investigated the drag of several components of parachute suspension systems commonly used for personnel and cargo airdrops. Specifically, the team determined drag coefficients for Type III nylon cord, 1000 lb spectra, and Type VII nylon webbing between Re = 400 to Re = 7,000, and tensions varying between 10 lbs and 55 lbs. All tests were conducted at an angle of attack of 90°. The momentum deficit method was used to determine the drag for each test configuration, and these were compared against baseline measurements of a 1/8 in diameter right circular cylindrical rod and a 2 in wide metal band. Close control of the pitot-static system yielded an uncertainty of approximately 10% for the calculations. The C'd for the Type III nylon cord ranged from .78 to 1.22, while for the spectra values remained close to a mean value of .70 over the range of tested conditions. Coefficient of drag data for the Type VII webbing closely matched the corresponding values for the metal band. A vortex shedding analysis did not indicate any synchronization with the natural frequency of the suspension lines, and the characteristic vortex shedding.

关键词： Parachutes

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