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6th IEEE International Conference on engineering, Technologies and Applied Sciences, ICETAS 2019

作者： Angeline, Lorita Choong, Mei Yeen Tan, Min Keng Liau, Chung Fan Chin, Renee Ka Yin Teo, Kenneth Tze Kin Modelling Simulation Computing Laboratory Artificial Intelligence Research Unit Faculty of Engineering Universiti Malaysia Sabah Kota Kinabalu Malaysia

ISBN: (数字)9781728140827

ISBN: (纸本)9781728140827

Following another vehicle too close is known as tailgating. Tailgater may not have enough space and time to avoid a collision. Thus there is a need for a fundamental understanding on factors affecting safe distance between vehicles. This paper aims to study such factors and to adopt certain rules and principles into the proposed traffic cellular automata model. Rule of seconds is applied and some deductions are made to attain a realistic traffic model. The simulation also entail human reaction time in perceiving safe distance with the leading vehicle and the simulation results are as expected. However there is a trade off between reaction time and an optimum safe following distance. Hence ideal reaction time of 0.75s is selected to emulate real life traffic flow without deteriorating traffic stability. © 2019 IEEE.

关键词： Cellular automata

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Using AI libraries for Incompressible Computational Fluid Dynamics

arXiv

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arXiv 2024年

作者： Chen, Boyang Heaney, Claire E. Pain, Christopher C. Applied Modelling and Computation Group Department of Earth Science and Engineering Imperial College London SW7 2AZ United Kingdom Centre for AI-Physics Modelling Imperial-X Imperial College London W12 7SL United Kingdom Novel Reservoir Modelling and Simulation Group Department of Earth Science and Engineering Imperial College London London United Kingdom Data Assimilation Laboratory Data Science Institute Imperial College London SW7 2AZ United Kingdom

Recently, there has been a huge effort focused on developing highly efficient open source libraries to perform Artificial Intelligence (AI) related computations on different computer architectures (for example, CPUs, GPUs and new AI processors). This has not only made the algorithms based on these libraries highly efficient and portable between different architectures, but also has substantially simplified the entry barrier to develop methods using AI. Here, we present a novel methodology to bring the power of both AI software and hardware into the field of numerical modelling by repurposing AI methods, such as Convolutional Neural Networks (CNNs), for the standard operations required in the field of the numerical solution of Partial Differential Equations (PDEs). The aim of this work is to bring the high performance, architecture agnosticism and ease of use into the field of the numerical solution of PDEs. We use the proposed methodology to solve the advection-diffusion equation, the non-linear Burgers equation and incompressible flow past a bluff body. For the latter, a convolutional neural network is used as a multigrid solver in order to enforce the incompressibility constraint. We show that the presented methodology can solve all these problems using repurposed AI libraries in an efficient way, and presents a new avenue to explore in the development of methods to solve PDEs and Computational Fluid Dynamics problems with implicit methods. © 2024, CC BY.

关键词： Computational fluid dynamics

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Iris-Based Biometric Identification Using a Combination of the Right - Left Iris Statistical Features 12

Iris-Based Biometric Identification Using a Combination of t...

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12th International Conference on Mathematical Modeling in Physical Sciences, IC-MSQUARE 2023

作者： Dincǎ Lǎzǎrescu, A.M. Moldovanu, S. Moraru, L. The Modelling & Simulation Laboratory Dunarea de Jos University of Galati 47 Domneasca Street Galati800008 Romania Mihail Kogǎlniceanu High School 161B Brǎilei St. Galati800320 Romania Department of Computer Science and Information Technology Faculty of Automation Computers Electrical Engineering and Electronics Dunarea de Jos University of Galati 47 Domneasca Street Galati800008 Romania Department of Chemistry Physics & Environment Faculty of Sciences and Environment Dunarea de Jos University of Galati 47 Domneasca Street Galati800008 Romania

A combination between the information extracted for both right iris and left iris could increase the efficacy of the biometric recognition systems. In this paper, we propose a biometric identification method based on density of image patterns extracted from human iris images and the combination and comparison of the right iris and the left iris characteristics. The density of the patters approach for processed images can be a new biometric feature used to implement a biometric recognition system with high performance when a small feature dimension is used. In this way, we can maximize the retention of the effective biometric information. The experiments were conducted on the MMU Iris Database containing 225 images of the left eye and 225 images of the right eye. Two morphological Top-hat and Hit or Miss transforms were implemented to find out the particular pattern of pixels. They allow for the enhancement of detail in images. Then, a statistical feature extraction technique is employed to derive the density of the patterns in morphological transformed images. To assess the density of the patterns differences between the right and left iris data groups, the Pearson's correlation coefficient (PCC) is computed. We reported very good results with a PCC of 0.6164 (strong and positive correlation) for Top-hat morphological operation whilst the Hit or Miss transform returns a PCC of 0.0127 so there is no relationship between the density of the patterns in the right and left irises. © 2024 Institute of Physics Publishing. All rights reserved.

关键词： Biometrics

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Enhancing Digital Twins with Advances in simulation and Artificial Intelligence: Opportunities and Challenges 23

Enhancing Digital Twins with Advances in Simulation and Arti...

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Proceedings of the Winter simulation Conference

作者： Simon J. E. Taylor Charles M. Macal Andrea Matta Markus Rabe Susan M. Sanchez Guodong Shao Modelling & Simulation Group Department of Computer Science Brunel University London Uxbridge UK Decision & Infrastructure Sciences Division Argonne National Laboratory Lemont USA Department of Mechanical Engineering Politecnico di Milano Milano Italy Department IT in Production and Logistics TU Dortmund University Dortmund Germany Operations Research Department Naval Postgraduate School Monterey USA Engineering Laboratory National Institute of Standards and Technology Gaithersburg USA

ISBN: (纸本)9798350369663

simulations are used to investigate physical systems. A digital twin goes beyond this by connecting a simulation with the physical system with the purpose of analyzing and controlling that system in real-time. In the past 5 years there has been a substantial increase in research into simulation and Artificial Intelligence (AI). The combination of simulation with AI presents many possible innovations. Similarly, combining AI with simulation presents further possibilities including approaches to developing trustworthy and explainable AI methods, solutions to problems arising from sparce or no data and better methods for time series analysis. Given the progress that has been made in Digital Twins and simulation and AI, what opportunities are there from combining these two exciting research areas? What challenges need to be overcome to achieve these? This article discusses these from the perspectives of six leading members of the Modeling & simulation community.

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Advancing Weed Detection in Agricultural Landscapes Using Computer Vision

Advancing Weed Detection in Agricultural Landscapes Using Co...

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IEEE International Conference on Artificial Intelligence in engineering and Technology (IICAIET)

作者： Bei Ren Tan Ervin Moung Muhd. Nur Afnan Uda Kenneth Tze Kin Teo Lorita Angeline School of Computer Science Taylor's University Subang Jaya Malaysia Faculty of Computing and Informatics Universiti Malaysia Sabah Kota Kinabalu Malaysia Faculty of Engineering Universiti Malaysia Sabah Kota Kinabalu Malaysia Modelling Simulation & Computing Laboratory Faculty of Engineering Universiti Malaysia Sabah Kota Kinabalu Malaysia

This paper explores the need for weed detection in agricultural landscapes, where weed infestations pose significant crop productivity challenges. To address this matter, computer vision techniques are utilised to create a weed detection algorithm that accurately detects weed patches inside agricultural field images. To ensure reliable model evaluation, the dataset is split into training and testing subsets before being fed into the YOLOv3 model. The YOLOv3 model performs well in terms of precision, with an average precision of 66.4 % for crop regions and a notable precision of 92.5% for detecting weeds. These results highlight the potential of artificial intelligence-driven weed detection techniques to optimize crop management practices and foster sustainable agriculture in the modern era. This research advances precision agriculture by effectively addressing weed infestations, paving the way for more efficient and targeted weed control strategies, which ultimately lead to increased crop yield and improved agricultural sustainability.

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Chaotic dynamics of granules-beam coupled vibration: Route and threshold

arXiv

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arXiv 2024年

作者： Li, Hang Li, Jian Fei, Hongzhu Hong, Guangyang Dong, Jinlu Yu, Aibing Key Laboratory of Structural Dynamics of Liaoning Province College of Sciences Northeastern University Shenyang110819 China ARC Research Hub for Computational Particle Technology Department of Chemical Engineering Monash University ClaytonVIC3800 Australia Centre for Simulation and Modelling of Particulate Systems Monash-Southeast University Joint Research Institute Suzhou China

Although granular materials are the second most processed in industry after water, the theoretical study of granules-structure interactions is not as advanced as that of fluid-structure interactions due to the lack of a unified view of the constitutive relation of granular materials. In the previous work [1], the theoretical model of granules-beam coupled vibration was developed and verified by experiments. However, it was also found that the system exhibits significant stiffness-softening Duffing characteristics even under micro-vibration, which implies that chaotic responses may be reached under certain conditions. To reveal the route and critical conditions for the system to enter chaos, in the present work, the chaotic dynamics of the system are studied. In qualitative analysis, Melnikov method is applied to analyze the instability behavior of the perturbed heteroclinic orbit of the system, thus the critical condition for the system to enter Smale horseshoe chaos, i.e., the Melnikov criterion, is obtained. The validity of the criterion is verified numerically. In experimental studies, the existence of chaotic responses and the route to chaos for granules-beam coupled vibrations is revealed. The experimental results suggest that the system response first experiences symmetry-breaking then undergoes a complete period-doubling cascade, and finally enters single-scroll chaos. In addition, although the Additional Dynamic Load (ADL) generated by granular media is highly complicated, a general and simple evolution pattern of the chaos threshold is found by parametric experiments, which is also supported by the Melnikov criterion. In short, the chaotic dynamics of granules-beam coupled vibration is revealed, which is a contribution to the engineering vibration aspect. On the theoretical side, an impressive result lies in that for the first time, the Melnikov criterion of such fractional-order systems is obtained in a global and closed form, which provides, respectively,

关键词： Granulation

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Optimization & control strategy for offshore wind turbine based on a dual fed induction generator

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Materials Today: Proceedings 2022年 58卷 1470-1475页

作者： Benyachou, B. Bahrar, B. Moufakkir, A. Gueraoui, K. Saidi Hassani Alaoui, M. Team of Modelling and Simulation of Mechanical and Energetic Faculty of Sciences Mohammed V University Rabat Morocco Equipe de mécanique des fluides et environnement ENSET Mohammedia Laboratoire Physique de la Matière Condensée et Energies Renouvelables FST Mohammedia Université Hassan II Casablanca Morocco Team Thermodynamic - Energy Energy Research Center Faculty of Sciences Mohammed V University Rabat Morocco Engineering Sciences and Applications Laboratory ENSAH d'Al Hocima Abdelmalek Essaadi University Morocco

This work is motivated by the progression of wind farms installed in the world and by the will of researchers and specialists to develop techniques and solutions to solve the problem of their integration into the electrical grid. To have maximum converted power, the turbine velocity must be adapted to the wind speed. This is a challenge for manufacturers and researchers who face difficulties in designing powerful and reliable operating point control devices at maximum power. This paper has tried to find a solution that can extract the maximum power generated by the wind turbine and improve its efficiency. For this purpose, several control strategies have been implemented, such as the Maximum Power Point Tracking (MPPT) strategy with velocity control that extracts the maximum power from the wind turbine, the pitch control to limit the aerodynamic power, and the direct torque control of the generator to control the electromagnetic torque and rotor flux. The simulation results obtained in this work show the relevance of optimizing the energy transfer in the wind turbine system. They also show that the use of control strategies contributes greatly to the improvement of the overall energy efficiency of the wind power system used. © 2022

关键词： Energy efficiency

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Enhancing Digital Twins with Advances in simulation and Artificial Intelligence: Opportunities and Challenges

Enhancing Digital Twins with Advances in Simulation and Arti...

引用

2023 Winter simulation Conference, WSC 2023

作者： Taylor, Simon J. E. MacAl, Charles M. Matta, Andrea Rabe, Markus Sanchez, Susan M. Shao, Guodong Brunel University London Modelling & Simulation Group Department of Computer Science UxbridgeUB8 3PH United Kingdom Argonne National Laboratory Decision & Infrastructure Sciences Division LemontIL60439 United States Politecnico di Milano Department of Mechanical Engineering Via La Masa 1 Milano20156 Italy Tu Dortmund University Department It in Production and Logistics Leonhard-Euler-Straße 5 Dortmund44227 Germany Naval Postgraduate School Operations Research Department 1 University Circle MontereyCA93943 United States National Institute of Standards and Technology Engineering Laboratory 100 Bureau Drive GaithersburgMD20899 United States

ISBN: (纸本)9798350369663

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Planting area and production decreased for winter-triticeae crops but increased for rapeseed in Ukraine with climatic impacts dominating

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Geography and Sustainability 2025年第2期6卷 108-116页

作者： Jichong Han Yuchuan Luo Zhao Zhang Jialu Xu Yi Chen Senthold Asseng Jonas Jägermeyr Christoph Müller Jørgen E Olesen Reimund Rötter Fulu Tao Joint International Research Laboratory of Catastrophe Simulation and Systemic Risk Governance School of National Safety and Emergency ManagementBeijing Normal UniversityZhuhai 519087China School of Systems science Beijing Normal UniversityBeijing 100875China Chongqing Jinfo Mountain Karst Ecosystem National Observation and Research Station School of Geographical SciencesSouthwest UniversityChongqing 400715China Key Laboratory of Land Surface Pattern and Simulation Institute of Geographical Sciences and Natural Resources ResearchChinese Academy of SciencesBeijing 100101China Technical University of Munich Department of Life Science EngineeringDigital AgricultureHEF World Agricultural Systems CenterFreisingGermany NASA Goddard Institute for Space Studies New YorkNYUSA Columbia University Center for Climate Systems ResearchNew YorkNYUSA Potsdam Institute for Climate Impacts Research(PIK) Member of the Leibniz AssociationPotsdamGermany Department of Agroecology Aarhus UniversityTjeleDenmark University of Götingen Tropical Plant Production and Agricultural Systems Modelling(TROPAGS)GötingenGermany University of Götingen Centre for Biodiversity and Sustainable Land Use(CBL)GötingenGermany College of Resources and Environment University of Chinese Academy of SciencesBeijing 100049China

On-time mapping dynamics of crop area,yield,and production is important for global food *** information,however,is often not ***,we used satellite information,a spectral-phenology integration approach for mapping crop area,and a machine learning model for predicting yield in the war-stricken *** found that in Ukraine crop area and production declined in 2022 relative to 2017–2021 and 2021 for wintertriticeae crops,which was invaded before the cropping season in February of that *** the same time,crop area and production for rapeseed increased in Ukraine,with yields consistently lower by 6.5%relative to *** low precipitation and the Russian-Ukrainian conflict-related factors contributed to such yield variations by-1.3%and-0.9%for winter-triticeae crops and-4.2%and-0.5%for rapeseed in *** demonstrate a robust framework for monitoring country-wide crop production dynamics in near real-time,serving as an early-foodsecurity-warning system.

关键词： Food security Conflict Machine learning Production Satellite

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Adapting Perturbation Voltage in PV Array with Power Point Tracking and Differential Evolution 6

Adapting Perturbation Voltage in PV Array with Power Point T...

引用

6th IEEE International Conference on engineering, Technologies and Applied Sciences, ICETAS 2019

作者： Kamaruddin, Nurul Izyan Haron, Ahmad Razani Tan, Min Keng Yang, Soo Siang Goh, Hui Hwang Teo, Kenneth Tze Kin Modelling Simulation Computing Laboratory Artificial Intelligence Research Unit Faculty of Engineering Universiti Malaysia Sabah Kota Kinabalu Malaysia School of Electrical Engineering Guangxi University Nanning China

ISBN: (纸本)9781728140827

The power output of photovoltaic array may reduce as the photovoltaic panels' connection close to each other and lead to the occurrence of partials shading. Under partial shading condition, the unshaded modules of PV array receive solar irradiation at higher level, while the shaded module of PV array receives lower irradiation. Thus, multiple maximum power point also will occur under the partial shading condition. The proposed modelling in this paper is 4×4 PV array and tested two different conditions in partial shading condition (PSC) where there are random irradiance values that had been set. Therefore, this paper aim to model more than one PV array and the platform modelling for this paper is 4×4 PV array. Besides that, explore the conventional method which is Perturb and Observe (PO) based MPPT controller in optimizing the efficiency of the PV array. Unfortunately, the conventional method only can trap the power at the local maximum power under partial shading conditions. Thus, the proposed algorithm that used to track the maximum power is differential evolution (DE) in order to improve the power output of the PV array. The simulation results shows the proposed DE able to track the global MPP. © 2019 IEEE.

关键词： Maximum power point trackers

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