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SSRN 2024年

作者： Bartwal, Naman Roy, Somnath Vanka, Surya Pratap Department of Mechanical Engineering Indian Institute of Technology Kharagpur West Bengal Kharagpur721302 India Center for Computational & Data Sciences Indian Institute of Technology Kharagpur West Bengal Kharagpur721302 India Department of Mechanical Science and Engineering University of Illinois at Urbana-Champaign UrbanaIL61801 United States

Thermal management of Li-ion batteries has attracted worldwide attention due to their widesp-read usage ranging from electronics to electric vehicles. To gain maximum performance from the battery pack, it is of utmost importance to limit the maximum temperature of Li-ion cells much below the safe working limit. In the present study, we use a high-order polyharmonic spline radial basis function (PHS-RBF) based multidomain meshless algorithm to study the distribution of temperature in the battery pack for discharge rate varying from 1C-5C. It is seen that for higher discharge rates (i.e. discharge rate $\geq$ 3C), active cooling method (air cooling) is insufficient to limit the working temperature of the battery pack to the safe operating limit. Hence, we cover each Li-ion cell with a layer of PCM. We study the effect of coolant inlet velocity and thickness of PCM on the temperature distribution within the battery pack. We present the variation of average and maximum temperature of batteries and the distribution of temperature in individual cells. The temperature distribution is not axisymmetric in most of the cells, especially for the cells located in the upstream portion of the battery pack. The highest temperatures are found in the cells located in the downstream portion of the battery pack. For effective battery pack management, the minimum PCM thickness required is determined to be 2 mm for a 3C discharge rate and 3 mm for a 4C discharge rate. However, at 5C, the PCM melts completely at all PCM thicknesses taken into consideration. For cases where Li-ion cells are covered by a layer of PCM, there is no significant change with the increase in coolant inlet velocity. © 2024, The Authors. All rights reserved.

关键词： Temperature control

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Physics-Informed Geometric Operators to Support Surrogate, Dimension Reduction and Generative Models for engineering Design

arXiv

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arXiv 2024年

作者： Khan, Shahroz Masood, Zahid Usama, Muhammad Kostas, Konstantinos Kaklis, Panagiotis Chen, Wei Wayne BAR Technologies Portsmouth United Kingdom Department of Mechanical and Aerospace Engineering Nazarbayev University Astana Kazakhstan Department of Naval Architecture Ocean and Marine Engineering University of Strathclyde Glasgow United Kingdom Division: Numerical Analysis & Computational Science Group: Data Science Heraklion Crete Greece J. Mike Walker’66 Department of Mechanical Engineering Texas A&M University TX United States

In this work, we propose a set of physics-informed geometric operators (GOs) to enrich the geometric data provided for training surrogate/discriminative models, dimension reduction, and generative models, typically employed for performance prediction, dimension reduction, and creating data-driven parameterisations, respectively. However, as both the input and output streams of these models consist of low-level shape representations, they often fail to capture shape characteristics essential for performance analyses. Therefore, the proposed GOs exploit the differential and integral properties of shapes—accessed through Fourier descriptors, curvature integrals, geometric moments, and their invariants—to infuse high-level intrinsic geometric information and physics into the feature vector used for training, even when employing simple model architectures or low-level parametric descriptions. We showed that for surrogate modelling, along with the inclusion of the notion of physics, GOs enact regularisation to reduce over-fitting and enhance generalisation to new, unseen designs. Furthermore, through extensive experimentation, we demonstrate that for dimension reduction and generative models, incorporating the proposed GOs enriches the training data with compact global and local geometric features. This significantly enhances the quality of the resulting latent space, thereby facilitating the generation of valid and diverse designs. Lastly, we also show that GOs can enable learning parametric sensitivities to a great extent. Consequently, these enhancements accelerate the convergence rate of shape optimisers towards optimal solutions. © 2024, CC BY-NC-SA.

关键词： Sensitivity analysis

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Social network analysis of manga: similarities to real-world social networks and trends over decades

arXiv

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arXiv 2023年

作者： Sugishita, Kashin Masuda, Naoki Department of Transdisciplinary Science and Engineering Tokyo Institute of Technology Tokyo152-8550 Japan Department of Mathematics State University of New York at Buffalo BuffaloNY14260-2900 United States Computational and Data-Enabled Science and Engineering Program State University of New York at Buffalo BuffaloNY14260-5030 United States Center for Computational Social Science Kobe University Kobe657-8501 Japan

Manga, Japanese comics, has been popular on a global scale. Social networks among characters, which are often called character networks, may be a significant contributor to their popularity. We collected data from 162 popular manga that span over 70 years and analyzed their character networks. First, we found that many of static and temporal properties of the character networks are similar to those of real human social networks. Second, the character networks of most manga are protagonist-centered such that a single protagonist interacts with the majority of other characters. Third, the character networks for manga mainly targeting boys have shifted to denser and less protagonist-centered networks and with fewer characters over decades. Manga mainly targeting girls showed the opposite trend except for the downward trend in the number of characters. The present study, which relies on manga data sampled on an unprecedented scale, paves the way for further population studies of character networks and other aspects of comics. Copyright © 2023, The Authors. All rights reserved.

关键词： Population statistics

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CMM PLN at MentalRiskES: A Traditional Machine Learning Approach for Detection of Eating Disorders and Depression in Chat Messages

CMM PLN at MentalRiskES: A Traditional Machine Learning Appr...

引用

2023 Iberian Languages Evaluation Forum, IberLEF 2023

作者： Guerra, Rodrigo Pizarro, Benjamín Muñoz-Castro, Carlos Carvallo, Andrés Rojas, Matías Aracena, Claudio Dunstan, Jocelyn Center for Mathematical Modeling Universidad de Chile Chile Faculty of Physical and Mathematical Sciences Universidad de Chile Chile Department of Computer Science Pontificia Universidad Católica de Chile Santiago Chile National Center for Artificial Intelligence Chile Institute for Mathematical and Computational Engineering Pontificia Universidad Católica de Chile Chile Millenium Institute Foundational Research on Data Chile

This paper describes our approaches to solving the MentalRiskES task, which belongs to the IberLEF (Iberian Languages Evaluation Forum) shared task. The task aims to identify the eating disorders and depression of a user using a series of Telegram messages. Our proposed system uses the traditional TFiDF method to represent the messages and then utilizes these representations as input for machine learning models. The best results for classification were obtained using the Naive Bayes classifier, while in the regression task, the best models were Gradient Boots Regressor and Linear Regressor. Despite its simplicity, we demonstrated that our traditional approaches can still achieve competitive results in recent NLP tasks, obtaining the best results in the case of detecting depression and eating disorders. © 2023 Copyright for this paper by its authors. Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0).

关键词： Natural language processing systems

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The Berkeley Single Cell computational Microscopy (BSCCM) dataset

arXiv

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arXiv 2024年

作者： Pinkard, Henry Liu, Cherry Nyatigo, Fanice Fletcher, Daniel A. Waller, Laura Department of Electrical Engineering and Computer Sciences University of California Berkeley United States Berkeley Institute for Data Science United States University of California San Francisco Bakar Computational Health Sciences Institute United States Department of Bioengineering University of California Berkeley United States

computational microscopy, in which hardware and algorithms of an imaging system are jointly designed, shows promise for making imaging systems that cost less, perform more robustly, and collect new types of information. Often, the performance of computational imaging systems, especially those that incorporate machine learning, is sample-dependent. Thus, standardized datasets are an essential tool for comparing the performance of different approaches. Here, we introduce the Berkeley Single Cell computational Microscopy (BSCCM) dataset, which contains over 12,000,000 images of 400,000 of individual white blood cells. The dataset contains images captured with multiple illumination patterns on an LED array microscope and fluorescent measurements of the abundance of surface proteins that mark different cell types. We hope this dataset will provide a valuable resource for the development and testing of new algorithms in computational microscopy and computer vision with practical biomedical applications. © 2024, CC BY.

关键词： Imaging systems

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Enhancing Sustainable Development Goals Through Future Vapor Pressure Deficit Analysis In The Nile River Basin

Enhancing Sustainable Development Goals Through Future Vapor...

引用

IEEE International Symposium on Geoscience and Remote Sensing (IGARSS)

作者： Surendra Maharjan Wenzhao Li Shahryar Fazli Hani Sewilam Hesham El-Askary Computational and Data Sciences Graduate Program Schmid College of Science and Technology Chapman University Orange CA USA Earth Systems Science and Data Solutions Lab Chapman University Orange CA USA The Center for Applied Research on the Environment and Sustainability The American University in Cairo Cairo Egypt Department of Engineering Hydrology RWTH Aachen University Aachen Germany Department of Environmental Sciences Faculty of Science Alexandria University Alexandria Egypt

ISBN: (数字)9798350360325

ISBN: (纸本)9798350360332

Vapor Pressure Deficit (VPD) is crucial in meteorology and agriculture for understanding plant-environment interactions. Its application as an indicator in agricultural practices notably advances Sustainable Development Goals such as Zero Hunger (SDG 2) and Climate Action (SDG 13). This research focuses on the impact of climate change on agricultural productivity and food security in the Nile River Basin (NRB), emphasizing the role of VPD, temperature, and precipitation. Utilizing Coupled Model Intercomparison Project Phase 6 (CMIP6) datasets from NEX-GDDP-CMIP6, the study analyzes key climatic variables that influence agricultural conditions. The study applies the Mann-Kendall test to evaluate VPD trends from 2000 to 2060 under two Shared Socioeconomic Pathways (SSPs), SSP2-4.5 and SSP5-8.5. The study's findings on the implications of rising VPD levels in the Nile River Basin (NRB), particularly under the SSP 5-8.5 scenario, highlight a critical challenge for the region's agricultural productivity and food security. The increased VPD, indicative of drier conditions, leads to a moisture deficit for crops, potentially reducing agricultural yields. This scenario poses a significant threat to food security, as lower crop yields can result in food shortages and higher food prices, adversely affecting vulnerable populations. The study underscores the necessity of integrating VPD insights into agricultural and water resource management strategies to uphold food security against climatic variations in support of the SDGs.

关键词： Productivity Climate change Precipitation Food security Agriculture Rivers Sustainable development

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Big data Analytics for Predictive Maintenance in Smart Grids and Energy Management Systems

Big Data Analytics for Predictive Maintenance in Smart Grids...

引用

International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud) (I-SMAC)

作者： Divya Nimma Sakshi Malik A. Balakumar Computational Science University of Southern Mississippi Data Analyst in UMMC USA Jindal Global Business School O.P. Jindal Global University Sonipat Haryana India Department of ECE K. Ramakrishnan College of Engineering Trichy India

ISBN: (数字)9798350376425

ISBN: (纸本)9798350376432

The application of wind power within smart grids is crucial thereby mandating integrative energy change. Yet, the randomness of wind and technological nature of wind turbines lead to quite a number of problems regarding the dependability and performance of supplied energy. These issues can be managed through the help of predictive maintenance which reduces the time that is taken in the machinery’s periodic maintenance while at the same time reduces the cost of the overall maintenance. The following research work puts forward a framework for developing deep learning models to improve the approaches to maintain the wind energy systems using LSTM networks. The framework is based on the Wind Turbine SCADA dataset which is a collection of time-series of various parameters of the turbine like wind speed, power output, rotor speed, temperature, and vibration and aims at predicting the probable equipment failures in future. The LSTM network used for the diagnosis of mechanical problems learns from the sensor data and watches for anomalies in real-time. Thus, owing to the organization of the maintenance activities according to such predictions, the framework minimizes the unexpected downtimes, and increases the lifespan of the turbine components, as well as the reliability of the energy production. In addition, the proposed business incorporates the predictive maintenance system into the smart grid system to facilitate energy management and the synchronization of the maintenance system with grid functionality. The research also responds to important issues: the fluctuation in the wind energy data and the adaptability of an LSTM model to large power stations.

关键词： Vibrations Temperature sensors Wind energy Wind speed Wind power generation Wind turbines Maintenance Smart grids Long short term memory Predictive maintenance

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Adaptive fast-reaching nonsingular terminal sliding mode tracking control for quadrotor UAVs subject to model uncertainties and external disturbances

引用

Ain Shams engineering Journal 2023年第8期14卷

作者： Mobayen, Saleh El-Sousy, Fayez F.M. Alattas, Khalid A Mofid, Omid Fekih, Afef Rojsiraphisal, Thaned Graduate School of Intelligent Data Science National Yunlin University of Science and Technology 123 University Road Section 3 Douliou Yunlin640301 Taiwan Department of Electrical Engineering Prince Sattam Bin Abdulaziz University Al Kharj Saudi Arabia Department of Computer Science and Artificial Intelligence College of Computer Science and Engineering University of Jeddah Jeddah Saudi Arabia Department of Electrical and Computer Engineering University of Louisiana at Lafayette Lafayette United States Advanced Research Center for Computational Simulation Department of Mathematics Faculty of Science Chiang Mai University Chiang Mai50200 Thailand Data Science Research Center Department of Mathematics Faculty of Science Chiang Mai University Chiang Mai50200 Thailand

This paper proposes an adaptive fast-reaching nonsingular terminal sliding mode control approach for the position and attitude tracking control of a quadrotor UAV subject to model uncertainty and external disturbances. To this end, a fast-reaching nonsingular terminal sliding surface is defined with the aim of fast convergence of the tracking error. The fast reachability of the nonsingular terminal sliding surface is proven using the Lyapunov stability theory. Since, in practice, the upper bounds of model uncertainties and external disturbances are unknown, an adaptive control scheme is considered to approximate them. The fast-reaching nonsingular terminal sliding mode control approach was augmented with the adaptive scheme to ensure both, the fast convergence of the switching surfaces and the rejection of model uncertainties and external disturbances. The effectiveness of the proposed adaptive fast-reaching nonsingular terminal sliding mode control approach is assessed using simulations of a quadrotor system implemented in MATLAB/Simulink software. The obtained results are further compared to those of an existing approach in terms of tracking performance, robustness, and integrator of absolute-value of error criteria. © 2022 THE AUTHORS

关键词： Unmanned aerial vehicles (UAV)

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Validating the information technology (IT) implementation framework to Implement mHealth technology for consumers: A case study of the Sense2Quit app for smoking cessation

引用

International Journal of Medical Informatics 2025年 202卷 105977-105977页

作者： Brin, Maeve Fontalvo, Sydney Hu, David Cioe, Patricia Huang, Ming-Chun Xu, Wenyao Schnall, Rebecca Columbia University School of Nursing New YorkNY United States Brown University School of Public Health United States Department of Data and Computational Science Duke Kunshan University Jiangsu China Department of Computer Science & Engineering University at Buffalo the State University of New York BuffaloNY United States Columbia University School of Public Health New YorkNY United States

Objective: The goal of this paper was to understand the applicability of the Information Technology (IT) Implementation Framework, a multi-level approach to identify factors that impede or promote IT usage, for incorporating a mHealth technology for consumers in the community setting. Methods: A case study of the implementation of the Sense2Quit App for smoking cessation among people living with HIV was examined to parse out the factors within the framework that are applicable to mHealth technology and the factors that may need modification for use of this framework within this context. Results: Findings suggest that phases two through five of the framework were applicable to our study and phase one was not. Conclusion: Findings support the use of the theory for implementation of mHealth technology for promoting consumer health at the community level. This use case may be useful for stakeholders evaluating implementation of mHealth for patients with chronic conditions as it highlights the need to identify preferences of app specifications, personal habits, and various factors such as confidentiality and digital literacy which may challenge sustained usage. © 2025 Elsevier B.V.

关键词： mHealth

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Unbiased Approximations for Stationary Distributions of McKean-Vlasov SDEs

arXiv

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arXiv 2024年

作者： Awadelkarim, Elsiddig Chada, Neil K. Jasra, Ajay Applied Mathematics and Computational Science Program Computer Electrical and Mathematical Sciences and Engineering Division King Abdullah University of Science and Technology Thuwal23955-6900 Saudi Arabia Department of Mathematics City University of Hong Kong Hong Kong School of Data Science The Chinese University of Hong Kong Shenzhen Shenzhen China

We consider the development of unbiased estimators, to approximate the stationary distribution of Mckean-Vlasov stochastic differential equations (MVSDEs). These are an important class of processes, which frequently appear in applications such as mathematical finance, biology and opinion dynamics. Typically the stationary distribution is unknown and indeed one cannot simulate such processes exactly. As a result one commonly requires a time-discretization scheme which results in a discretization bias and a bias from not being able to simulate the associated stationary distribution. To overcome this bias, we present a new unbiased estimator taking motivation from the literature on unbiased Monte Carlo. We prove the unbiasedness of our estimator, under assumptions. In order to prove this we require developing ergodicity results of various discrete time processes, through an appropriate discretization scheme, towards the invariant measure. Numerous numerical experiments are provided, on a range of MVSDEs, to demonstrate the effectiveness of our unbiased estimator. Such examples include the Currie-Weiss model, a 3D neuroscience model and a parameter estimation problem. © 2024, CC BY-NC-SA.

关键词： Stochastic systems

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