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Multiscale Dynamical Indices Reveal Scale-Dependent Atmospheric Dynamics

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arXiv 2024年

作者： Dong, Chenyu Messori, Gabriele Faranda, Davide Gualandi, Adriano Lucarini, Valerio Mengaldo, Gianmarco College of Design and Engineering National University of Singapore Singapore Department of Earth Sciences Uppsala University Sweden Uppsala University Sweden Department of Meteorology Bolin Centre for Climate Research Stockholm University Sweden LSCE Université Paris-Saclay France London Mathematical Laboratory United Kingdom IPSL École Normale Supérieure France Department of Earth Sciences University of Cambridge Istituto Nazionale di Geofisica e Vulcanologia Italy School of Computing and Mathematical Sciences University of Leicester United Kingdom

Geophysical systems are inherently complex and span multiple spatial and temporal scales, making their dynamics challenging to understand and predict. This challenge is especially pronounced for extreme events, which are primarily governed by their instantaneous properties rather than their average characteristics. Advances in dynamical systems theory, including the development of local dynamical indices such as local dimension and inverse persistence, have provided powerful tools for studying these short-lasting phenomena. However, existing applications of such indices often rely on predefined fixed spatial domains and scales, with limited discussion on the influence of spatial scales on the results. In this work, we present a novel spatially multiscale methodology that applies a sliding window method to compute dynamical indices, enabling the exploration of scale-dependent properties. Applying this framework to high-impact European summertime heatwaves, we reconcile previously different perspectives, thereby underscoring the importance of spatial scales in such analyses. Furthermore, we emphasize that our novel methodology has broad applicability to other atmospheric phenomena, as well as to other geophysical and spatio-temporal systems. Copyright © 2024, The Authors. All rights reserved.

关键词： Inverse problems

Interventional video grounding with dual contrastive learning

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arXiv 2021年

作者： Nan, Guoshun Qiao, Rui Xiao, Yao Liu, Jun Leng, Sicong Zhang, Hao Lu, Wei StatNLP Research Group Singapore University of Technology and Design Singapore Singapore Shanghai Jiao Tong University China Information Systems Technology and Design Singapore University of Technology and Design Singapore Singapore School of Computer Science and Engineering Nanyang Technological University Singapore Singapore Institute of High Performance Computing A*STAR Singapore Singapore

Video grounding aims to localize a moment from an untrimmed video for a given textual query. Existing approaches focus more on the alignment of visual and language stimuli with various likelihood-based matching or regression strategies, i.e., P(Y |X). Consequently, these models may suffer from spurious correlations between the language and video features due to the selection bias of the dataset. 1) To uncover the causality behind the model and data, we first propose a novel paradigm from the perspective of the causal inference, i.e., interventional video grounding (IVG) that leverages backdoor adjustment to deconfound the selection bias based on structured causal model (SCM) and do-calculus P(Y |do(X)). Then, we present a simple yet effective method to approximate the unobserved confounder as it cannot be directly sampled from the dataset. 2) Meanwhile, we introduce a dual contrastive learning approach (DCL) to better align the text and video by maximizing the mutual information (MI) between query and video clips, and the MI between start/end frames of a target moment and the others within a video to learn more informative visual representations. Experiments on three standard benchmarks show the effectiveness of our approaches. Our code is available on GitHub: https://***/nanguoshun/IVG. © 2021, CC BY.

关键词： Calculations

Optimizing wastewater treatment plant operations: a machine learning approach for energy consumption and climate dynamics analysis

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Optimizing wastewater treatment plant operations: a machine ...

8th IET Smart Cities Symposium (SCS 2024)

作者： Mahmoud Elshabrawy Faris H. Rizk Ahmed Mohamed Zaki Marwa M. Eid Ali E. Takieldeen Abdelhameed Ibrahim Abdelaziz A. Abdelhamid Laith Abualigah El-Sayed M. El-kenawy Computer Science and Intelligent Systems Research Center Blacksburg 24060 Virginia USA Faculty of Artificial Intelligence Delta University for Science and Technology Mansoura 35111 Egypt School of ICT Faculty of Engineering Design and Information & Communications Technology (EDICT) Bahrain Polytechnic PO Box 33349 Isa Town Bahrain Department of Computer Science College of Computing and Information Technology Shaqra University 11961 Shaqra Saudi Arabia Hourani Center for Applied Scientific Research Al-Ahliyya Amman University Amman 19328 Jordan

ISBN: (数字)9781837243105

Treatment plant optimization plays an important role in the implementation of eco-problem solutions. This article is going to cover how machine learning algorithms can determine energy consumption, climate, and wastewater features of electricity at a wastewater treatment plant in eastern Melbourne from 2014 to 2019. This study uses data obtained from the Melbourne Water and Airport weather station, which are freely available to carry out MLPRegressor, SVM, Linear Regression, Decision Tree Regression, random forest regression, and Nearest Neighbor. Through customary measures like MSE, RMSE, EVS, and others, the best model is adequately identified, which is the Random Forest Regressor model, which has 0.889285. (Lowest MSE) With these results, the plant treatment optimization processes, such as sampling for environmental analysis and the control of energy consumption, have improved.

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Bidirectional approximate message passing for ris-assisted multi-user MISO communications

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arXiv 2021年

作者： Wei, Li Huang, Chongwen Guo, Qinghua Zhang, Zhaoyang Debbah, Mérouane Yuen, Chau Singapore University of Technology and Design Singapore487372 Singapore Department of Information and Electronic Engineering Zhejiang University China School of Electrical Computer and Telecommunications Engineering University of Wollongong Wollongong Australia Lagrange Mathematics and Computing Research Center Paris75007 France

Reconfigurable intelligent surfaces (RISs) have been recently considered as a promising candidate for energy-efficient solutions in future wireless networks. Their dynamic and low-power configuration enables coverage extension, massive connectivity, and low-latency communications. Due to a large number of unknown variables referring to the RIS unit elements and the transmitted signals, channel estimation and signal recovery in RIS-based systems are the ones of the most critical technical challenges. To address this problem, we focus on the RIS-assisted multi-user wireless communication system and present a joint channel estimation and signal recovery algorithm in this paper. Specifically, we propose a bidirectional approximate message passing algorithm that applies the Taylor series expansion and Gaussian approximation to simplify the sum-product algorithm in the formulated problem. Our simulation results show that the proposed algorithm shows the superiority over a state-of-art benchmark method. We also provide insights on the impact of different RIS parameter settings on the proposed algorithms. Copyright © 2021, The Authors. All rights reserved.

关键词： Signal reconstruction

Data gap/outlier correction and treatment

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AIP Conference Proceedings 2024年第1期3034卷

作者： Juan Zuluaga Michael Castillo Divya Syal Andres Calle Navid Shaghaghi Ethical Pragmatic and Intelligent Computing (EPIC) Research Laboratory and the Healthcare Innovation and Design (HID) Program Departments of Computer Science and Engineering (CSEN) and Bioengineering (BIOE) of the School of Engineering (SoE) at Santa Clara University (SCU) in Santa Clara California USA

The prevalence of gaps and outliers within datasets presents substantial challenges, particularly in the realm of time series fore-casting and various other predictive machine learning (ML) tasks. This paper, introduces an effective technique for correcting gaps and outliers in data and validates the approach by applying it to datasets with outlier zones drawn from three diverse contexts. This innovative technique holds promising potential to enhance the performance of machine learning models by treating the data to alleviate the complications posed by these issues and in doing so contributes a valuable tool to the data science toolbox.

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Optimal Minimum Energy Path Planning of Mobile Robot Based on Improved WOA-GA with Hybrid Strategy for Community-Centric Application

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Optimal Minimum Energy Path Planning of Mobile Robot Based o...

2023 International Conference on Machine Learning and Cybernetics, ICMLC 2023

作者： Du, Jiang Da-Lin, Zhou Gong-Fa, Li Bao-Li, Lu Jun-Tong, Yun Ying, Liu Wuhan University of Science and Technology Key Laboratory of Metallurgical Equipment and Control Technology Ministry of Education Wuhan430081 China School of Computing University of Portsmouth PortsmouthPO1 3HE United Kingdom China Three Gorges University Hubei Key Laboratory of Hydroelectric Machinery Design & Maintenance Yichang443002 China Wuhan University of Science and Technology Key Laboratory of Mechanical Transmission and Manufacturing Engineering of Hubei Province Wuhan430081 China Precision Manufacturing Research Institute Wuhan University of Science and Technology Wuhan430081 China Institute of Semiconductors Chinese Academy of Sciences Beijing100083 China Research Center for Biomimetic Robot and Intelligent Measurement and Control Wuhan University of Science and Technology Wuhan430081 China

ISBN: (纸本)9798350303780

The path planning of mobile robots is investigated to minimize energy loss in intelligent manufacturing. To achieve optimal energy consumption planning, this paper proposes a hybrid strategy that enhances the whale optimization algorithm (WOA) and the genetic algorithm (GA). The WOA-GA algorithm combines their respective advantages and effectively mitigates premature convergence exhibited by the standard traditional algorithm. To enhance the global and local search capabilities of the standard WOA, we employ adaptive weighting and a Cauchy mutation strategy. Additionally, we introduce an adaptive crossover mutation probability and an elite strategy to mitigate the detrimental effects of the genetic algorithm's evolutionary operation in the late iterations, thereby improving its performance. This paper compares the performance of the standard GA, the standard WOA-GA algorithm, and the enhanced WOA-GA algorithm. The experimental results demonstrate that the enhanced WOA-GA algorithm can achieve optimal energy-efficient path planning using the hybrid strategy. The average energy consumption of the enhanced WOA-GA algorithm can be reduced by 30%, while the maximum energy consumption can be reduced by 47%. The results confirm the effectiveness and feasibility of the proposed method in enhancing the level of green manufacturing. © 2023 IEEE.

关键词： Genetic algorithms

Secure and Reliable Parking Protocol Based on Blockchain for VANETs

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Secure and Reliable Parking Protocol Based on Blockchain for...

IEEE Conference on Wireless Communications and Networking

作者： Yan Zhang Lei Zhang Burong Kang Yue Ma Tong Chen Engineering Research Center of Software/Hardware Co-design Technology and Application Ministry of Education East China Normal University Shanghai China Shanghai Key Laboratory of Trustworthy Computing School of Software Engineering East China Normal University Shanghai China

ISBN: (纸本)9781728195056;9781728195063

With the development of vehicular ad hoc network (VANET) technology, more and more smart parking systems in VANETs are presented. However, existing solutions suffer from the challenges of dishonest parking lots that may claim there are more empty spots than they actually have, malicious occupation of parking spots and multi-reservation attack, etc. To address these challenges, we propose a secure and reliable smart parking protocol based on blockchain and linkable group signatures. For the security of our scheme, it not only realizes traditional authentication, privacy preservation and message confidentiality requirements but also prevents multi-reservation attack and the dishonest parking lots that claim more empty spots than they actually have.

关键词： Privacy Protocols Conferences Vehicular ad hoc networks Authentication Blockchain Reliability

Heterogeneous message passing for heterogeneous networks

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arXiv 2023年

作者： Cantwell, George T. Kirkley, Alec Radicchi, Filippo Santa Fe Institute 1399 Hyde Park Road Santa FeNM87501 United States Institute of Data Science University of Hong Kong Hong Kong Department of Urban Planning and Design University of Hong Kong Hong Kong Urban Systems Institute University of Hong Kong Hong Kong Center for Complex Networks and Systems Research School of Informatics Computing and Engineering Indiana University BloomingtonIN47408 United States

Message passing (MP) is a computational technique used to find approximate solutions to a variety of problems defined on networks. MP approximations are generally accurate in locally tree-like networks but require corrections to maintain their accuracy level in networks rich with short cycles. However, MP may already be computationally challenging on very large networks and additional costs incurred by correcting for cycles could be prohibitive. We show how the issue can be addressed. By allowing each node in the network to have its own level of approximation, one can focus on improving the accuracy of MP approaches in a targeted manner. We perform a systematic analysis of 109 real-world networks and show that our node-based MP approximation is able to increase both the accuracy and speed of traditional MP approaches. We find that, compared to conventional MP, a heterogeneous approach based on a simple heuristic is more accurate in 81% of tested networks, faster in 64% of cases, and both more accurate and faster in 49% of cases. Copyright © 2023, The Authors. All rights reserved.

关键词： Message passing

Green production and consumption of textiles and apparel: Importance, fabrication, challenges and future prospects

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Journal of Open Innovation: Technology, Market, and Complexity 2024年第2期10卷

作者： Rahaman, Md. Tareque Pranta, Arnob Dhar Repon, Md. Reazuddin Ahmed, Md. Samin Islam, Tarekul Department of Textile Engineering Mawlana Bhashani Science and Technology University Santosh Tangail 1902 Bangladesh Department of Textile Engineering Daffodil International University Dhaka 1216 Bangladesh Department of Bioproducts and Biosystems School of Chemical Engineering Aalto University Espoo 02150 Finland Department of Production Engineering Faculty of Mechanical Engineering and Design Kaunas University of Technology Studentų 56 Kaunas LT-51424 Lithuania Department of Statistics Mawlana Bhashani Science and Technology University Santosh Tangail 1902 Bangladesh Department of Computing John Moores University Liverpool United Kingdom Department of Materials Science and Engineering King Fahd University of Petroleum and Minerals Dhahran 31261 Saudi Arabia ZR Research Institute for Advanced Materials Sherpur 2100 Bangladesh

Textile and garments production involves a wide range of steps, beginning with the spinning of fibers into yarn, then manufacturing to fabric and finally, adding value-enhancing treatments like washing, dyeing and finishing to the outfits. Frequently, these manufacturing processes contravene the overarching tenets of environmental viability. Compounded by escalating demand for apparel products, manufacturers exhibit diminished enthusiasm for the implementation of ecologically conscientious and sustainable production methodologies. Therefore, the fast swings in fashion trends and the shortening of vogue cycles are major accelerators for the disruption of ecological balance. In more recent times, a profusion of pioneering initiatives and advancements have been instigated to sustainable remedies within the production and consumption paradigms of the contemporary clothing sector. Moreover, sustainable techniques within the apparel sector encompass not just environmentally friendly supply chain control, but also the facilitation of a cost-effective and socially agreeable production setup. Future considerations and developments in sustainability in spinning, fabric production, wet processing, and garment manufacturing are explored in this review article. It delves into environmental issues and the ways in which modern clothing brands promote sustainable technologies and materials. © 2024 The Authors

关键词： Assessment of life cycle Consumption Production Recycling Sustainable Textiles