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arXiv 2023年

作者： Margot, Jean-Luc Li, Megan G. Pinchuk, Pavlo Myhrvold, Nathan Lesyna, Larry Alcantara, Lea E. Andrakin, Megan T. Arunseangroj, Jeth Baclet, Damien S. Belk, Madison H. Bhadha, Zerxes R. Brandis, Nicholas W. Carey, Robert E. Cassar, Harrison P. Chava, Sai S. Chen, Calvin Chen, James Cheng, Kellen T. Cimbri, Alessia Cloutier, Benjamin Combitsis, Jordan A. Couvrette, Kelly L. Coy, Brandon P. Davis, Kyle W. Delcayre, Antoine F. Du, Michelle R. Feil, Sarah E. Fu, Danning Gilmore, Travis J. Grahill-Bland, Emery Iglesias, Laura M. Juneau, Zoe Karapetian, Anthony G. Karfakis, George Lambert, Christopher T. Lazbin, Eric A. Li, Jian H. Li, Zhuofu Liskij, Nicholas M. Lopilato, Anthony V. Lu, Darren J. Ma, Detao Mathur, Vedant Minasyan, Mary H. Muller, Maxwell K. Nasielski, Mark T. Nguyen, Janice T. Nicholson, Lorraine M. Niemoeller, Samantha Ohri, Divij Padhye, Atharva U. Penmetcha, Supreethi V. Prakash, Yugantar Qi, Xinyi Rindt, Liam Sahu, Vedant Scally, Joshua A. Scott, Zefyr Seddon, Trevor J. Shohet, Lara-Lynn V. Sinha, Anchal Sinigiani, Anthony E. Song, Jiuxu Stice, Spencer M. Tabucol, Nadine M. Uplisashvili, Andria Vanga, Krishna Vazquez, Amaury G. Vetushko, George Villa, Valeria Vincent, Maria Waasdorp, Ian J. Wagaman, Ian B. Wang, Amanda Wight, Jade C. Wong, Ella Yamaguchi, Natsuko Zhang, Zijin Zhao, Junyang Lynch, Ryan S. Department of Earth Planetary and Space Sciences University of California Los AngelesCA90095 United States Department of Physics and Astronomy University of California Los AngelesCA90095 United States National Renewable Energy Laboratory GoldenCO80401 United States Intellectual Ventures 3150 139th Ave SE BellevueWA98005 United States LXL Technology Las VegasNV89148 United States UCLA Samueli School of Engineering University of California Los AngelesCA90095 United States Department of Mathematics University of California Los AngelesCA90095 United States Department of Electrical Engineering University of California Los AngelesCA90095 United States Department of Public Affairs University of California Los AngelesCA90095 United States Department of Electrical and Computer Engineering University of California Los AngelesCA90095 United States Department of Computer Science University of California Los AngelesCA90095 United States Department of Materials Engineering University of California Los AngelesCA90095 United States UCLA College of Letters and Science University of California Los AngelesCA90095 United States Department of Mechanical Engineering University of California Los AngelesCA90095 United States Department of Aerospace Engineering University of California Los AngelesCA90095 United States Department of Neuroscience University of California Los AngelesCA90095 United States Green Bank Observatory P.O. Box 2 Green BankWV24494 United States

We conducted a search for narrowband radio signals over four observing sessions in 2020–2023 with the L-band receiver (1.15–1.73 GHz) of the 100 m diameter Green Bank Telescope. We pointed the telescope in the directions of 62 TESS Objects of Interest, capturing radio emissions from a total of ∼11,680 stars and planetary systems in the ∼9 arcminute beam of the telescope. All detections were either automatically rejected or visually inspected and confirmed to be of anthropogenic nature. We also quantified the end-to-end efficiency of radio SETI pipelines with a signal injection and recovery analysis. The UCLA SETI pipeline recovers 94.0% of the injected signals over the usable frequency range of the receiver and 98.7% of the injections when regions of dense radio frequency interference are excluded. In another pipeline that uses incoherent sums of 51 consecutive spectra, the recovery rate is ∼15 times smaller at ∼6%. The pipeline efficiency affects calculations of transmitter prevalence and SETI search volume. Accordingly, we developed an improved Drake Figure of Merit and a formalism to place upper limits on transmitter prevalence that take the pipeline efficiency and transmitter duty cycle into account. Based on our observations, we can state at the 95% confidence level that fewer than 6.6% of stars within 100 pc host a transmitter that is detectable in our search (EIRP > 1013 W). For stars within 20,000 ly, the fraction of stars with detectable transmitters (EIRP > 5 × 1016 W) is at most 3 × 10−4. Finally, we showed that the UCLA SETI pipeline natively detects the signals detected with AI techniques by Ma et al. (2023). © 2023, CC BY-NC-SA.

关键词： Transmitters

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Prediction of Occupational Physical Activities using Inertial Measurement Units and Deep Learning Models 64th

Prediction of Occupational Physical Activities using Inertia...

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64th International Annual Meeting of the Human Factors and Ergonomics Society, HFES 2020

作者： Yan, Yishu Fan, Hao Li, Yibin Hoeglinger, Elias Wiesinger, Alexander Barr, Alan Adamson, Carisa Harris Department of Mechanical Engineering University of California Berkeley United States Department of Industrial Design Northwestern Polytechnic China Department of Electrical Engineering and Computer Science University of California Berkeley United States University of Applied Sciences Upper Austria Linz Austria Department of Medicine University of California San Francisco United States School of Public Health University of California Berkeley United States

Many workers engaged in manual material handling (MMH) jobs experience high physical demands that are associated with work-related musculoskeletal disorders (WMSD). Quantifying the physical demands of a job is an important legal requirement in the US that is used by human resources in the job hiring process. Most physical demands analysis (PDA) are performed using observational and semi-quantitative methods. The lack of accuracy and reliability of these methods can create problems when assigning acceptable tasks to an injured worker. In this study, various deep learning models were applied to data from eight inertial measurement units (IMUs) to predict 15 occupational physical activities (OPA). Overall, a 95% accuracy was reached by convolutional neural network (CNN) for predicting occupational physical activities when performed in isolation. More work is needed to estimate the accuracy of the model when OPA elements are combined into a more complex task. © 2020 by Human Factors and Ergonomics Society. All rights reserved.

关键词： Forecasting

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A Continuous Improvement Instrument for the evaluationof the ergonomics management system in the supply chain

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Heliyon 2024年第24期10卷 e40956页

作者： Rodríguez-Gámez, Iván Francisco Maldonado-Macías, Aide Aracely Lagarda-Leyva, Ernesto A. Hernández-Arellano, Juan Luis Rodríguez, Yordán Departament of Electrical Engineering and Computer Sciences Autonomous University of Ciudad Juarez Del Charro Ave. 450N Chihuahua Ciudad Juarez Mexico Departament of Industrial Engineering and Manufacturing Autonomous University of Ciudad Juarez Del Charro Ave. 450N Chihuahua Ciudad Juarez Mexico Department of Industrial Engineering Sonora Institute of Technology 5 de Febrero 818 Sur Col. Centro Sonora Obregón Mexico Departament of Design Autonomous University of Ciudad Juarez Del Charro Ave. 450N Ciudad Juarez Chihuahua Mexico National School of Public Health University of Antioquia Medellin Colombia

Nowadays, organizations must comply with high-quality standards, health and safety regulations, and socially sustainable practices to succeed in a globalized world. Supply Chains (SC) enable them to satisfy their customers' needs for quality products just in time and at the best price. However, management systems (MS) need to be improved to identify, evaluate, and control ergonomic risks, which opens a research opportunity for Ergonomics Management Systems (EMS) as they apply to sustainable SCs. This study aims to design and validate an instrument to assess the EMS within a SC using a continuous improvement approach. The study used convenience sampling as experts were invited by e-mail, at congresses, and through a digital platform. A response rate of 6.2 % was obtained from the latter, and a total of 34 experts responded to the instrument. An exploratory factor analysis (EFA) and a confirmatory factor analysis (CFA) were also carried out for the constructs of PLAN, DO, CHECK, and ACT. Finally, factors and variables were reduced by 42.71 %, leaving a 46-item final version of the instrument. Most of the structural model fit indices for the sample demonstrated good values, and the reliability indices were acceptable, this confirming the overall reliability of the instrument. In conclusion, the instrument was validated for all proposed constructs, with the exception of the PLAN construct. Thus, the instrument was found to be relevant and fit for implementation in EMS. © 2024

关键词： Confirmatory factor analysis Continuous improvement approach Ergonomics management system Exploratory factor analysis Supply chain

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A Multi-Perspective Machine Learning Approach to Evaluate Police-Driver Interaction in Los Angeles

arXiv

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arXiv 2024年

作者： Graham, Benjamin A.T. Brown, Lauren Chochlakis, Georgios Dehghani, Morteza Delerme, Raquel Friedman, Brittany Graeden, Ellie Golazizian, Preni Hebbar, Rajat Hejabi, Parsa Kommineni, Aditya Salinas, Mayagüez Sierra-Arévalo, Michael Trager, Jackson Weller, Nicholas Narayanan, Shrikanth Department of Political Science and International Relations University of Southern California Los Angeles90007 United States School of Public Policy University of Southern California Los Angeles90007 United States University of Southern California Los Angeles90007 United States Department of Computer Science University of Southern California Los Angeles90007 United States Brain and Creativity Institute University of Southern California Los Angeles90007 United States Department of Sociology University of Southern California Los Angeles90007 United States Center for Global Health Science and Security Georgetown University WashingtonDC20057 United States Department of Electrical and Computer Engineering University of Southern California Los Angeles90007 United States The Lewis Registry Los AngelesCA90049 United States Department of Sociology The University of Texas at Austin Austin78712 United States Department of Psychology University of Southern California Los Angeles90007 United States Department of Political Science University of California Riverside Riverside92521 United States

Interactions between the government officials and civilians affect public wellbeing and the state legitimacy that is necessary for the functioning of democratic society. Police officers, the most visible and contacted agents of the state, interact with the public more than 20 million times a year during traffic stops. Today, these interactions are regularly recorded by body-worn cameras (BWCs), which are lauded as a means to enhance police accountability and improve police-public interactions. However, the timely analysis of these recordings is hampered by a lack of reliable automated tools that can enable the analysis of these complex and contested police-public interactions. This article proposes an approach to developing new multi-perspective, multimodal machine learning (ML) tools to analyze the audio, video, and transcript information from this BWC footage. Our approach begins by identifying the aspects of communication most salient to different stakeholders, including both community members and police officers. We move away from modeling approaches built around the existence of a single ground truth and instead utilize new advances in soft labeling to incorporate variation in how different observers perceive the same interactions. We argue that this inclusive approach to the conceptualization and design of new ML tools is broadly applicable to the study of communication and development of analytic tools across domains of human interaction, including education, medicine, and the workplace. Copyright © 2024, The Authors. All rights reserved.

关键词： Machine learning

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Transatlantic partnership on artificial intelligence: realities, perceptions and future implications

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Global Affairs 2020年第4-5期6卷 537-557页

作者： Muhammed Can Halid Kaplan a Department of International Relations and Public Administration University of Minho Braga Portugal b Department of Electrical and Computer Engineering University of Texas at San Antonio San Antonio USA

ABSTRACTABSTRACTRecent confrontation between China and the US laid bare underlying factors that might accelerate decoupling in different realms. Technology is one of the main factors of recent rift. Specific to AI, democratic countries are striving for finding common ground to counter diffusion of authoritarian technologies. In this paper we argue that future AI alliance/partnership has to find a solution in three distinct political obstacles. Firstly, future alliance/partnership bear in mind the crumbling the US leadership. The US leadership is must, for the future of alliance/partnership due to its economic and technological prowess. Secondly, the EU's fragmentation in deploying Chinese technology and their dependency towards China not only technologically but also economically will be determinative factor for the success of alliance/partnership. Finally, democratic partners and allies should focus on creating mechanisms to offer AI-based technologies to both offset authoritarian counterparts and to become more competitive.

关键词： Artificial intelligence AI policy alliances technology policy US foreign policy the EU fragmentation

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Machine learning based potentiating impacts of 12-lead ECG for classifying paroxysmal versus non-paroxysmal atrial fibrillation

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International Journal of Arrhythmia 2022年第1期23卷 1-9页

作者： Sungsoo Kim Alan C. Bovik Sohee Kwon Sung-Hwi Hong JunYong Kim Boyoung Joung Hui-Nam Pak Moon-Hyeong Lee Mia K. Markey Hye Jin Hwang Junbeom Park Electrical and Computer Engineering The University of Texas at Austin Austin USA Deparment of Internal Medicine College of Medicine Yonsei University Seoul South Korea Department of Epidemiology Harvard T. H. Chan School of Public Health Boston MA USA Harvard University Cambridge USA Department of Biomedical Engineering The University of Texas at Austin Austin USA Department of Imaging Physics The University of Texas MD Anderson Cancer Center Houston USA Cardiovascular Division Department of Medicine Beth Israel Deaconess Medical Center Boston MA USA Department of Cardiology College of Medicine Ewha Womans University 1071 Annyangcheon-ro Yangcheon-gu Seoul Republic of Korea

BackgroundConventional modality requires several days observation by Holter monitor to differentiate atrial fibrillation (AF) between Paroxysmal atrial fibrillation (PAF) and Non-paroxysmal atrial fibrillation (Non-PA... 详细信息

Background

Conventional modality requires several days observation by Holter monitor to differentiate atrial fibrillation (AF) between Paroxysmal atrial fibrillation (PAF) and Non-paroxysmal atrial fibrillation (Non-PAF). Rapid and practical differentiating approach is needed.

Objective

To develop a machine learning model that observes 10-s of standard 12-lead electrocardiograph (ECG) for real-time classification of AF between PAF versus Non-PAF.

Methods

In this multicenter, retrospective cohort study, the model training and cross-validation was performed on a dataset consisting of 741 patients enrolled from Severance Hospital, South Korea. For cross-institutional validation, the trained model was applied to an independent data set of 600 patients enrolled from Ewha University Hospital, South Korea. Lasso regression was applied to develop the model.

Results

In the primary analysis, the Area Under the Receiver Operating Characteristic Curve (AUC) on the test set for the model that predicted AF subtype only using ECG was 0.72 (95% CI 0.65–0.80). In the secondary analysis, AUC only using baseline characteristics was 0.53 (95% CI 0.45–0.61), while the model that employed both baseline characteristics and ECG parameters was 0.72 (95% CI 0.65–0.80). Moreover, the model that incorporated baseline characteristics, ECG, and Echocardiographic parameters achieved an AUC of 0.76 (95% CI 0.678–0.855) on the test set.

Conclusions

Our machine learning model using ECG has potential for automatic differentiation of AF between PAF versus Non-PAF achieving high accuracy. The inclusion of Echocar

关键词： Machine learning 12 leads surface electrocardiogram Atrial fibrillation

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Incentivizing or Disincentivizing Participation in Demand Response Programs? Estimation of Customer Willingness to Accept

SSRN

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SSRN 2025年

作者： Wang, Yu Howard, Gregory Zhang, Wendong Brown, Marilyn Morton, Abigail Cetin, Kristen McCalley, James Department of Political Science Iowa State University United States Department of Economics East Carolina University United States The Charles H. Dyson School of Applied Economics and Management Cornell University United States School of Public Policy Georgia Institute of Technology United States Federal Energy Regulatory Commission United States Department of Civil and Environmental Engineering Michigan State University United States Department of Electrical and Computer Engineering Iowa State University United States

Demand response has great potential to provide value flexibility services to the grid, which can be harnessed through direct load control (DLC) programs. Many utilities have provided direct financial incentives to encourage residential customers to enroll in DLC programs. However, financial incentives do not always result in high participation rate. This study aims to assess residential customers’ willingness to enroll in utility-run DLC programs and analyze how incentives affect participation intention. A survey using the contingent valuation method (CVM) collected a random sample of 591 residents in the U.S. Midwest from 2020-2022, which finds, overall, 56.7% of residents are willing to enroll in DLC. It is estimated that 61.5% of residents are willing to participate due to intrinsic motivations (i.e., without monetary incentive), while a small token ($15-24 sign-on bonus) only leads to about 50% of the customers agreeing to enroll. To reach the same level of participation from intrinsic motivations, utilities must offer a much higher incentive - $83-$90. Additionally, we find several factors affect acceptance of DLC programs, including knowledge learning, concerns of comfort loss, and personal beliefs on energy savings, reliability, and environmental benefit. Findings from this study have significant policy implications and help improve the design of utility DLC programs. When developing strategies to recruit participants, no mention of monetary incentives could increase the participation of resident customers. We also recommend that utilities consider educational and demonstration programs to engage stakeholders, and information campaigns to emphasize the potential benefits without compromising thermal comfort. © 2025, The Authors. All rights reserved.

关键词： Sales

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Rate-induced tipping in complex high-dimensional ecological networks

arXiv

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arXiv 2023年

作者： Panahi, Shirin Do, Younghae Hastings, Alan Lai, Ying-Cheng School of Electrical Computer and Energy Engineering Arizona State University TempeAZ85287 United States Department of Mathematics Nonlinear Dynamics & Mathematical Application Center Kyungpook National University Daegu41566 Korea Republic of Department of Environmental Science and Policy University of California One Shields Avenue DavisCA95616 United States Santa Fe Institute 1399 Hyde Park Road Santa FeNM87501 United States Department of Physics Arizona State University TempeAZ85287 United States

In an ecosystem, environmental changes as a result of natural and human processes can cause some key parameters of the system to change with time. Depending on how fast such a parameter changes, a tipping point can occur. Existing works on rate-induced tipping, or R-tipping, offered a theoretical way to study this phenomenon but from a local dynamical point of view, revealing, e.g., the existence of a critical rate for some specific initial condition above which a tipping point will occur. As ecosystems are subject to constant disturbances and can drift away from their equilibrium point, it is necessary to study R-tipping from a global perspective in terms of the initial conditions in the entire relevant phase space region. In particular, we introduce the notion of the probability of R-tipping defined for initial conditions taken from the whole relevant phase space. Using a number of real-world, complex mutualistic networks as a paradigm, we discover a scaling law between this probability and the rate of parameter change and provide a geometric theory to explain the law. The real-world implication is that even a slow parameter change can lead to a system collapse with catastrophic consequences. In fact, to mitigate the environmental changes by merely slowing down the parameter drift may not always be effective: only when the rate of parameter change is reduced to practically zero would the tipping be avoided. Our global dynamics approach offers a more complete and physically meaningful way to understand the important phenomenon of R-tipping. © 2023, CC BY.

关键词： Ecosystems

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Three Different Directions in Which the European Union Could Replace Russian Natural Gas

SSRN

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SSRN 2023年

作者： Nikas, Alexandros Frilingou, Natasha Heussaff, Conall Fragkos, Panagiotis Mittal, Shivika Sampedro, Jon Giarola, Sara Sasse, Jan-Philipp Rinaldi, Lorenzo Doukas, Haris Gambhir, Ajay Giannousakis, Anastasis Golinucci, Nicolò Koasidis, Konstantinos Rocco, Matteo Vincenzo Trutnevyte, Evelina Xexakis, Georgios Zachmann, Georg Zisarou, Eleftheria Colombo, Emanuela Hawkes, Adam Yarlagadda, Brinda Binsted, Matthew Iyer, Gokul Van de Ven, Dirk-Jan Energy Policy Unit School of Electrical and Computer Engineering National Technical University of Athens Athens Greece Bruegel Brussels Belgium E3Modelling S.A. Athens Greece Grantham Institute for Climate Change and the Environment Imperial College London London United Kingdom Leioa Spain Department of Chemical Engineering Imperial College London London United Kingdom Section of Earth and Environmental Sciences University of Geneva Switzerland Department of Energy Politecnico di Milano Milan Italy HOLISTIC P.C. Athens Greece Joint Global Change Research Institute Pacific Northwest National Laboratory MD United States

Russia’s invasion of Ukraine fuelled an energy crisis, considerably impacting Europe given its heavy reliance on Russian natural gas. Based on four global integrated assessment models that are further soft-linked to two sectoral models, our study explores the trade-offs among three approaches to living without Russian gas in Europe: replacing with other gas imports, boosting domestic energy production, and accelerating energy efficiency. We find that substituting Russian gas from other trade partners would miss an opportunity to accelerate decarbonisation in end-use sectors while risking fossil-fuel lock-ins, despite featuring the lowest gas price spikes and reducing heating costs for end-users in the near term. Boosting domestic, primarily renewable, energy production would instead require considerable investments, potentially burdening consumers. Energy demand reductions, however, may offer more space for emissions cuts at the lowest power-sector investment costs;nonetheless, this strategy would also risk relocation of energy-intensive industries, an aspect of increasing policy relevance. © 2023, The Authors. All rights reserved.

关键词： Natural gas

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Spatio-temporal dynamics of malaria in Rwanda between 2012 and 2022: a demography-specific analysis

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Infectious Diseases of Poverty 2024年第5期13卷 100-100页

作者： Felix K.Rubuga Paula Moraga Ayman Ahmed Emmanuel Siddig Eric Remera Giovenale Moirano Guéladio Cissé Jürg Utzinger Swiss Tropical and Public Health Institute Allschwil Switzerland University of Basel Basel Switzerland College of Medicine and Health Sciences University of Rwanda Kigali Rwanda Center for Impact Innovation and Capacity building for Health Information systems and Nutrition (CIIC-HIN) Kigali Rwanda Institute of Endemic Diseases University of Khartoum Khartoum Sudan Computer Electrical and Mathematical Sciences and Engineering Division King Abdullah University of Science and Technology Thuwal Saudi Arabia Department of Medical Microbiology and Infectious Diseases Erasmus Medical Center University Medical Center Rotterdam Rotterdam The Netherlands Faculty of Medical Laboratory Sciences University of Khartoum Khartoum Sudan Rwanda Biomedical Center Kigali Rwanda Department of Medical Science University of Turin Torino Italy Barcelona Supercomputing Center Barcelona Spain

Background Despite global efforts to reduce and eventually interrupt malaria transmission,the disease remains a pressing public health problem,especially in sub-Saharan *** study presents a detailed spatio-temporal analysis of malaria transmission in Rwanda from 2012 to *** main objective was to gain insights into the evolving patterns of malaria and to inform and tailor effective public health *** The study used yearly aggregated data of malaria cases from the Rwanda health management information *** employed a multifaceted analytical approach,including descriptive statistics and spatio-temporal analysis across three demographic groups:children under the age of 5 years,and males and females above 5 *** spatially explicit models and spatio scan statistics were utilised to examine geographic and temporal patterns of relative risks and to identify clusters of malaria *** We observed a significant increase in malaria cases from 2014 to 2018,peaking in 2016 for males and females aged above 5 years with counts of 98,645 and 116,627,respectively and in 2018 for under 5-year-old children with 84,440 cases with notable geographic *** like Kamonyi(Southern Province),Ngoma,Kayonza and Bugesera(Eastern Province)exhibited high burdens,possibly influenced by factors such as climate,vector control practices,and cross-border *** spatially explicit modeling revealed elevated relative risks in numerous districts,underscoring the heterogeneity of malaria transmission in these districts,and thus contributing to an overall rising trend in malaria cases until 2018,followed by a subsequent *** findings emphasize that the heterogeneity of malaria transmission is potentially driven by ecologic,socioeconomic,and behavioural *** The study underscores the complexity of malaria transmission in Rwanda and calls for climate adaptive,gender-,age-and district-specific strategies in

关键词： Malaria transmission Epidemiology public health Rwanda Spatio-temporal analysis Rwanda

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