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Analysis of high-power packages for white-light-emitting diode lamps with remote phosphor

MRS Online Proceedings Library 2021年第1期892卷 166-171页

作者： Hong Luo Jong Kyu Kim Yangang Xi E. Fred Schubert Jaehee Cho Cheolsoo Sone Yongjo Park Department of Physics Applied Physics and Astronomy Rensselaer Polytechnic Institute Troy USA Electrical Computer and Systems Engineering Department Rensselaer Polytechnic Institute Troy USA Photonics Program Team Samsung Advanced Institute of Technology Suwon Korea

An optimized packaging configuration for high-power white-light-emitting diode (LED) lamps that employs a diffuse reflector cup, a remote phosphor and a hemi-spherically-shaped encapsulation is presented. Ray tracing simulations for this configuration show that the phosphor efficiency can be enhanced by up to 50% over conventional packages. It is experimentally shown that dichromatic LED lamps with remote phosphor and diffuse reflector cup configuration have higher phosphor efficiency by 15.4% for blue-pumped yellow phosphor and by 27% for ultraviolet-pumped blue phosphor over conventional packages. Those improvements are attributed to reduced absorption of the phosphorescence by the LED chip and the reduction of deterministic optical modes trapped inside the encapsulant.

关键词： packaging optoelectronic optical properties

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Mine-to-client planning with Markov Decision Process 18

Mine-to-client planning with Markov Decision Process

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18th European Control Conference, ECC 2020

作者： Leal Gomes Leite, Joao Marcelo Arruda, Edilson F. Bahiense, Laura Marujo, Lino G. Federal University of Rio de Janeiro Industrial Engineering Program Alberto Luiz Coimbra Institute Graduate School and Research in Engineering Rio de Janeiro Brazil Federal University of Rio de Janeiro Systems Engineer and Computer Science Program Alberto Luiz Coimbra Institute Graduate School and Research in Engineering Rio de Janeiro Brazil

ISBN: (纸本)9783907144015

This works presents an innovative application of Markov Decision Process (MDP) to a medium-term mining logistics planning problem considering the mine-to-client supply chain. We implemented three distinct algorithms based on state-of-the-art approaches to solve large-scale problems, and compared their results. Furthermore, we combined all three variants in a single novel algorithm that attained fast convergence and may be an alternative to circumvent the curse of dimensionality underlying large scale problems. © 2020 EUCA.

关键词： Supply chains

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FluxProg 2.0 - Teaching Introductory programming Using Flowcharts with Real and Simulated Robots for The Brazilian Robotics Olympiad (OBR)

FluxProg 2.0 - Teaching Introductory Programming Using Flowc...

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IEEE Latin American Robotics Symposium, LARS

作者： João Alberto Fabro Matheus Biscaya Gutierrez Fernando Henrique Ratusznei Caetano DAINF - Academic Department of Informatica PPGCA - Graduate Program on Applied Computing LASER-Laboratory for Advanced Robotics and Embedded Systems UTFPR - Federal University of Technology - Paraná Curitiba PR - Brazil Information Systems academic - UTFPR - Federal University of Technology - Paraná Curitiba PR - Brazil Computer Engineering academic - UTFPR - Federal University of Technology - Paraná Curitiba PR - Brazil

ISBN: (数字)9781665462808

ISBN: (纸本)9781665462815

In this paper, an approach to aid in introductory programming courses is presented, focused on students that had never had any contact with computer programming. The approach, that was introduced in a previous paper [3], presents programming concepts using icons and “flowcharts”, and a 3D robotics simulator (CoppeliaSim), that has free educational use. This time, a real version of the simulated robot, built using Arduino and cheap, easily obtainable electronic components, is also presented. The programs to control the robot are developed by graphically constructing flowcharts on the visual editor, and then following the execution of programs using the simulated (or real) robot, step by step. This graphic program editor is named “FluxProg”, and its 2nd version is now available online, with new features comprising variables, arithmetic and logic expressions, thus providing a complete programming environment.

关键词： Flowcharts Visualization Three-dimensional displays Conferences Education Electronic components Robots

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Gamma — General Abstract Model for Multiset mAnipulation and dynamic dataflow model: An equivalence study

Gamma — General Abstract Model for Multiset mAnipulation an...

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作者： Mello, Rui R. de Araújo, Leandro S. Alves, Tiago A. O. Marzulo, Leandro A. J. Paillard, Gabriel A. L. França, Felipe M. G. Program Systems Engineering and Computer Science Federal University of Rio de Janeiro Rio de Janeiro Brazil Brazilian Navy Research Institute Rio de Janeiro Brazil State University of Rio de Janeiro Rio de Janeiro Brazil Google Mountain ViewCA United States Virtual UFC Institute Federal University of Ceará Ceará Brazil

With the increase of the search for computational models where the expression of parallelism occurs naturally, some paradigms arise as options for the current generation of computers. In this context, dynamic dataflow and Gamma—General Abstract Model for Multiset mAnipulation—emerge as interesting computational model choices. In dynamic dataflow model, operations are performed as soon as their associated operands are available, without rely on a program Counter to dictate the execution order of instructions. The Gamma paradigm is based on a parallel multiset rewriting scheme. It provides a nondeterministic execution model inspired by an abstract chemical machinemetaphor, where operations are formulated as reactions that occur freely among matching elements belonging to the multiset. In this work, equivalence relations between the dynamic dataflow and Gamma paradigms are exposed and explored, while methods to convert from dataflow to Gamma paradigm and vice versa are provided. It is shown that vertices and edges of a dynamic dataflow graph can correspond, respectively, to reactions and multiset elements in the Gamma paradigm. This work provides the scientific community with the possibility of taking profit of both parallel programming models, contributing with a versatility component to researchers and developers. © 2021 John Wiley & Sons, Ltd.

关键词： Parallel programming

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Structured Downsampling for Fast, Memory-efficient Curation of Online Data Streams

arXiv

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arXiv 2024年

作者： Moreno, Matthew Andres Zaman, Luis Dolson, Emily Department of Ecology and Evolutionary Biology Ann Arbor United States Center for the Study of Complex Systems Ann Arbor United States Michigan Institute for Data and AI in Society Ann Arbor United States University of Michigan Ann Arbor United States Department of Computer Science and Engineering East Lansing United States Program in Ecology Evolution and Behavior East Lansing United States Michigan State University East Lansing United States

Operations over data streams typically hinge on efficient mechanisms to aggregate or summarize history on a rolling basis. For high-volume data steams, it is critical to manage state in a manner that is fast and memory efficient - particularly in resource-constrained or real-time contexts. Here, we address the problem of extracting a fixed-capacity, rolling subsample from a data stream. Specifically, we explore "data stream curation" strategies to fulfill requirements on the composition of sample time points retained. Our "DStream" suite of algorithms targets three temporal coverage criteria: (1) steady coverage, where retained samples should spread evenly across elapsed data stream history;(2) stretched coverage, where early data items should be proportionally favored;and (3) tilted coverage, where recent data items should be proportionally favored. For each algorithm, we prove worst-case bounds on rolling coverage quality. In contrast to previous work by Moreno, Rodriguez Papa, and Dolson (2024), which dynamically scales memory use to guarantee a specified level of coverage quality, here we focus on the more practical, application-driven case of maximizing coverage quality given a fixed memory capacity. As a core simplifying assumption, we restrict algorithm design to a single update operation: writing from the data stream to a calculated buffer site - with data never being read back, no metadata stored (e.g., sample timestamps), and data eviction occurring only implicitly via overwrite. Drawing only on primitive, low-level operations and ensuring full, overhead-free use of available memory, this "DStream" framework ideally suits domains that are resource-constrained (e.g., embedded systems), performance-critical (e.g., real-time), and fine-grained (e.g., individual data items as small as single bits or bytes). In particular, proposed power-of-two-based buffer layout schemes support O(1) data ingestion via concise bit-level operations. To further practical applica

关键词： Data streams

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Dish-Trend: Intervention Modeling Simulator That Accounts for Trend Influences

Dish-Trend: Intervention Modeling Simulator That Accounts fo...

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Simulation Winter Conference

作者： Stefan Andjelkovic Natasa Miskov-Zivanov Computational and Systems Biology Joint Carnegie Mellon University and University of Pittsburgh Computational Biology PhD Program University of Pittsburgh Pittsburgh PA USA Electrical and Computer Engineering Bioengineering Computational and Systems Biology University of Pittsburgh Pittsburgh PA USA

ISBN: (纸本)9781665433129

Simulation on directed graphs is an important method for understanding the dynamics in the systems where connectivity graphs contain cycles. Discrete Stochastic Heterogeneous Simulator (DiSH) is one of the simulation tools with wide application, which uses regulator values to calculate state updates of regulated elements. Here we present a new simulation approach DiSH-trend which also takes into account the trends in regulating elements. We demonstrate the features of trend-based regulation, as well as hybrid regulation, which is a combination of the trend- and level-based approaches. The modeling capabilities are demonstrated on a small toy model, showcasing different functionalities. Real-world capabilities are demonstrated on a larger network model of food insecurity in the Ethiopian region Oromia. Adding trend-based regulation to models results in increased modeling flexibility, and hybrid regulation improves qualitative dynamic behavior prediction. With appropriate data, DiSH-trend becomes a powerful tool for exploring intervention strategies.

关键词： Regulators Toy manufacturing industry Stochastic processes Predictive models Market research Regulation Data models

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Combining imitation and deep reinforcement learning to accomplish human-level performance on a virtual foraging task

arXiv

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arXiv 2022年

作者： Giammarino, Vittorio Dunne, Matthew F. Moore, Kylie N. Hasselmo, Michael E. Stern, Chantal E. Paschalidis, Ioannis Ch. Division of Systems Engineering Boston University BostonMA02446 United States Dept. of Electrical and Computer Engineering Boston University BostonMA02446 United States Dept. of Biomedical Engineering Boston University BostonMA02215 United States Cognitive Neuroimaging Center Boston University BostonMA02215 United States Graduate Program for Neuroscience Boston University BostonMA02215 United States Center for Systems Neuroscience Boston University BostonMA02215 United States

We develop a simple framework to learn bio-inspired foraging policies using human data. We conduct an experiment where humans are virtually immersed in an open field foraging environment and are trained to collect the highest amount of rewards. A Markov Decision Process (MDP) framework is introduced to model the human decision dynamics. Then, Imitation Learning (IL) based on maximum likelihood estimation is used to train Neural Networks (NN) that map human decisions to observed states. The results show that passive imitation substantially underperforms humans. We further refine the human-inspired policies via Reinforcement Learning (RL) using the on-policy Proximal Policy Optimization (PPO) algorithm which shows better stability than other algorithms and can steadily improve the policies pretrained with IL. We show that the combination of IL and RL can match human results and that good performance strongly depends on combining the allocentric information with an egocentric representation of the environment. © 2022, CC BY.

关键词： Reinforcement learning

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A Genetic Algorithm to Optimize Cargo Stability in Container Transportation

A Genetic Algorithm to Optimize Cargo Stability in Container...

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IEEE Global Conference on Consumer Electronics (GCCE)

作者： Chi-Jung Hsieh Kuang-Sung Wu Tin-Yu Wu Fu Jie Tey Yi-Kai Chen Jye Yi Ho Department of Computer Science and Information Engineering National Ilan University Ilan County Taiwan Master Program of E-Learning for Multimedia and Network Communications National Ilan University Yilan Taiwan Department of Management Information Systems National Pingtung University of Science and Technology Pingtung County Taiwan Department of Electrical Engineering National Taiwan University of Science and Technology Taipei Taiwan

ISBN: (纸本)9781665492331

In the era of the global village, frequent cross-border trade in goods has made container transportation a significant part in delivery of cargo. However, rollover accidents of container trucks often occur because of tall truck height, improper cargo stowage or crooked roads. Therefore, how to find the optimal center of gravity (CG) of the packed cargo remains an issue that the transportation industry should not neglect. To optimize cargo stability and reduce the incidence of rollovers, this paper proposes a genetic algorithm that scores the cargo stacking process to find the best CG of the cargo based on the CG of the vehicle. According to the deviation angle and the point closest to the best CG, we can Figure out the optimal cargo stacking method.

关键词： Rollover Transportation industry Roads Stacking Transportation Containers Safety

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Theory-guided randomized neural networks for decoding medication-taking behavior

Theory-guided randomized neural networks for decoding medica...

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2021 IEEE EMBS International Conference on Biomedical and Health Informatics, BHI 2021

作者： Kaur, Navreet Gonzales, Manuel Alcaraz, Cristian Garcia Barnes, Laura E. Wells, Kristen J. Gong, Jiaqi Department of Engineering Systems and Environment University of Virginia VA22904 United States SDSU UC San Diego Joint Doctoral Program in Clinical Psychology San DiegoCA92120 United States Department of Psychology San Diego State University San DiegoCA92182 United States Department of Computer Science The University of Alabama TuscaloosaAL35487 United States

ISBN: (纸本)9781665403580

Long-term endocrine therapy (e.g. Tamoxifen, aromatase inhibitors) is crucial to prevent breast cancer recurrence, yet rates of adherence to these medications are low. To develop, evaluate, and sustain future interventions, individual-level modeling can be used to understand breast cancer survivors' behavioral mechanisms of medication-taking. This paper presents interdisciplinary research, wherein a model employing randomized neural networks was developed to predict breast cancer survivors' daily medication-taking behavior based on their survey data over three time periods (baseline, 4 months, 8 months). The neural network structure was guided by random utility theory developed in psychology and behavioral economics. Comparative analysis indicates that the proposed model outperforms existing computational models in terms of prediction accuracy under conditions of randomness. © 2021 IEEE

关键词： Diseases

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Emergent dimer-model topological order and quasi-particle excitations in liquid crystals: combinatorial vortex lattices

arXiv

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arXiv 2025年

作者： Meng, Cuiling Wu, Jin-Sheng Kos, Žiga Dunkel, Jörn Nisoli, Cristiano Smalyukh, Ivan I. Department of Physics and Chemical Physics Program University of Colorado BoulderCO80309 United States Hiroshima University Hiroshima Higashihiroshima Japan Department of Mathematics Massachusetts Institute of Technology CambridgeMA02139 United States Faculty of Mathematics and Physics University of Ljubljana Ljubljana Slovenia Department of Condensed Matter Physics Jožef Stefan Institute Ljubljana Slovenia Theoretical Division Physics of Condensed Matter and Complex Systems Center For Nonlinear Studies Los Alamos National Laboratory Los AlamosNM87545 United States Department of Electrical Computer and Energy Engineering Materials Science and Engineering Program University of Colorado BoulderCO80309 United States Renewable and Sustainable Energy Institute National Renewable Energy Laboratory University of Colorado BoulderCO80309 United States

Liquid crystals have proven to provide a versatile experimental and theoretical platform for studying topological objects such as vortices, skyrmions, and hopfions. In parallel, in hard condensed matter physics, the concept of topological phases and topological order has been introduced in the context of spin liquids to investigate emergent phenomena like quantum Hall effects and high-temperature superconductivity. Here, we bridge these two seemingly disparate perspectives on topology in physics. Combining experiments and simulations, we show how topological defects in liquid crystals can be used as versatile building blocks to create complex, highly degenerate topological phases, which we refer to as ‘Combinatorial Vortex Lattices’ (CVLs). CVLs exhibit extensive residual entropy and support locally stable quasi-particle excitations in the form of charge-conserving topological monopoles, which can act as mobile information carriers and be linked via Dirac strings. CLVs can be rewritten and reconfigured on demand, endowed with various symmetries, and modified through laser-induced topological surgery — an essential capability for information storage and retrieval. We demonstrate experimentally the realization, stability, and precise optical manipulation of CVLs, thus opening new avenues for understanding and technologically exploiting higher-hierarchy topology in liquid crystals and other ordered media. Copyright © 2025, The Authors. All rights reserved.

关键词： Laser surgery

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