Relevant bibliographies by topics / Loss optimization

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Loss optimization'

Author: Grafiati
Published: 5 June 2025
Last updated: 2 August 2025

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Journal articles on the topic "Loss optimization"

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Fuchs, Marco, Cagatay Necati Dagli, and Stephan Kabelac. "Shape Optimization of Heat Exchanger Fin Structures Using the Adjoint Method and Their Experimental Validation." Energies 17, no. 5 (2024): 1246. http://dx.doi.org/10.3390/en17051246.

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The freedom of additive manufacturing allows for the production of heat-transferring structures that are optimized in terms of heat transfer and pressure loss using various optimization methods. One question is whether the structural optimizations made can be reproduced by additive manufacturing and whether the adaptations can also be verified experimentally. In this article, adjoint optimization is used to optimize a reference structure and then examine the optimization results experimentally. For this purpose, optimizations are carried out on a 2D model as well as a 3D model. The material ch
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Fulga, Cristinca. "Portfolio optimization under loss aversion." European Journal of Operational Research 251, no. 1 (2016): 310–22. http://dx.doi.org/10.1016/j.ejor.2015.11.038.

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Park, Kyungchul, and Kyungsik Lee. "Distribution-robust loss-averse optimization." Optimization Letters 11, no. 1 (2016): 153–63. http://dx.doi.org/10.1007/s11590-016-1002-z.

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Tsouvalas, Nikolaos, Ioannis Xydis, Ioannis Tsakirakis, and Z. Papazacharopoulos. "Asynchronous motor drive loss optimization." Journal of Materials Processing Technology 181, no. 1-3 (2007): 301–6. http://dx.doi.org/10.1016/j.jmatprotec.2006.03.062.

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Ahmad, Faris, Musirin Ismail, Jelani Shahrizal, Amri Ismail Saiful, Helmi Mansor Mohd, and V. Senthil Kumar A. "Tap changer optimisation using embedded differential evolutionary programming technique for loss control in power system." Bulletin of Electrical Engineering and Informatics 9, no. 6 (2020): 2253–60. https://doi.org/10.11591/eei.v9i6.2505.

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Over-compensation and under-compensation phenomena are two undesirable results in power system compensation. This will be not a good option in power system planning and operation. The non-optimal values of the compensating parameters subjected to a power system have contributed to these phenomena. Thus, a reliable optimization technique is mandatory to alleviate this issue. This paper presents a stochastic optimization technique used to fix the power loss control in a high demand power system due to the load increase, which causes the voltage decay problems leading to current increase and syst
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Dr.K., Lenin *1. "DIMENSIONED PARTICLE SWARM OPTIMIZATION FOR REACTIVE POWER OPTIMIZATION PROBLEM." International Journal of Research - Granthaalayah 6, no. 4 (2018): 281–90. https://doi.org/10.5281/zenodo.1248180.

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This paper present’s Dimensioned Particle Swarm Optimization (DPSO) algorithm for solving Reactive power optimization (RPO) problem. Dimensioned extension is introduced to particles in the particle swarm optimization (PSO) model in order to overcome premature convergence in interactive optimization. In the performance of basic PSO often flattens out with a loss of diversity in the search space as resulting in local optimal solution. Proposed algorithm has been tested in standard IEEE 57 test bus system and compared to other standard algorithms. Simulation results reveal about the best pe
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Kim, Minyoung, and Timothy Hospedales. "A Stochastic Approach to Bi-Level Optimization for Hyperparameter Optimization and Meta Learning." Proceedings of the AAAI Conference on Artificial Intelligence 39, no. 17 (2025): 17913–20. https://doi.org/10.1609/aaai.v39i17.33970.

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We tackle the general differentiable meta learning problem that is ubiquitous in modern deep learning, including hyperparameter optimization, loss function learning, few-shot learning and more. These problems are often formalized as Bi-Level Optimizations (BLO). We introduce a novel perspective by turning a given BLO problem into a stochastic optimization, where the inner loss function becomes a smooth probability distribution, and the outer loss becomes an expected loss over the inner distribution. To solve this stochastic optimization, we adopt Stochastic Gradient Langevin Dynamics (SGLD) MC
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Faris, Ahmad, Ismail Musirin, Shahrizal Jelani, Saiful Amri Ismail, Mohd Helmi Mansor, and A. V. Senthil Kumar. "Tap changer optimisation using embedded differential evolutionary programming technique for loss control in power system." Bulletin of Electrical Engineering and Informatics 9, no. 6 (2020): 2253–60. http://dx.doi.org/10.11591/eei.v9i6.2505.

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Over-compensation and under-compensation phenomena are two undesirable results in power system compensation. This will be not a good option in power system planning and operation. The non-optimal values of the compensating parameters subjected to a power system have contributed to these phenomena. Thus, a reliable optimization technique is mandatory to alleviate this issue. This paper presents a stochastic optimization technique used to fix the power loss control in a high demand power system due to the load increase, which causes the voltage decay problems leading to current increase and syst
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Yang, Zhenhuan, Wei Shen, Yiming Ying, and Xiaoming Yuan. "Stochastic AUC optimization with general loss." Communications on Pure & Applied Analysis 19, no. 8 (2020): 4191–212. http://dx.doi.org/10.3934/cpaa.2020188.

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Jourjon, Guillaume, Emmanuel Lochin, and Laurent Dairaine. "Optimization of TFRC Loss History Initialization." IEEE Communications Letters 11, no. 3 (2007): 276–78. http://dx.doi.org/10.1109/lcomm.2007.061707.

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Dissertations / Theses on the topic "Loss optimization"

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Thompson, Mark Richard. "Fixed point methods for loss networks /." St. Lucia, Qld, 2002. http://www.library.uq.edu.au/pdfserve.php?image=thesisabs/absthe16490.pdf.

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Kinney, Mark D. "General loss function applied to satellite scheduling optimization." Thesis, Monterey, California: Naval Postgraduate School, 2014. http://hdl.handle.net/10945/43938.

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Approved for public release; distribution is unlimited<br>Satellite imagery utilization is an oversubscribed problem and therefore requires optimum scheduling methodology to maximize the use of the systems. There are many methods to determine performance of a scheduling algorithm, many of which rely on comparison to already established standards. Based on Taguchi’s quality loss function formulation that was developed for the manufacturing industry, four general quality loss functions are presented. These loss functions show the dollars lost when two different performances are changed. The two
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Papier, Felix. "Optimization of rental systems : queuing loss theory for the optimization of cargo vehicle rental systems /." Köln : Kölner Wiss.-Verl, 2007. http://deposit.d-nb.de/cgi-bin/dokserv?id=3069373&prov=M&dok_var=1&dok_ext=htm.

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Teo, Koon Soon. "Loss of coordination in competitive supply chains." Thesis, Massachusetts Institute of Technology, 2009. http://hdl.handle.net/1721.1/54216.

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Thesis (S.M.)--Massachusetts Institute of Technology, Computation for Design and Optimization Program, 2009.<br>This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.<br>Cataloged from student submitted PDF version of thesis.<br>Includes bibliographical references (p. 161-163).<br>The loss of coordination in supply chains quantifies the inefficiency (i.e. the loss of total profit) due to the presence of competition in the supply chain. In this thesis, we discuss four models: one model with multiple reta
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Ottosson, Simon, and Fredrik Wahlgren. "Optimization of Cavity Receiver Geometry with regards to Radiation Heat Loss." Thesis, KTH, Industriell ekologi, 2016. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-189133.

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In order to maximize the e ciency of power generation in concentrated solar power systems (CSP) it is de- sired to achieve as high a tempera- ture in the receiver as possible due to the use of the Sterling cycle to gen- erate power. This report investigates three di↵erent geometries for cavity receivers in CSP systems; cylindrical, conical and truncated conical. The goal has been to minimize the heat loss due to radiation. This was achieved through mathematical mod- eling with the help of MATLAB. Five di↵erent cases with regards to oper- ating temperature and proportions of the receiver where
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Pedreira, Carlos Eduardo. "Theory of shape optimization with applications to heat loss minimization." Thesis, Imperial College London, 1987. http://hdl.handle.net/10044/1/47626.

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Ding, Qifeng. "Optimal meter placement and transaction-based loss allocation in deregulated power system operation." Texas A&M University, 2004. http://hdl.handle.net/1969.1/1475.

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In this dissertation topics of optimal meter placement and transaction-based loss allocation in deregulated power system operation are investigated. Firstly, Chapter II introduces the basic idea of candidate measurement identification, which is the selection of candidate measurement sets, each of which will make the system observable under a given contingency (loss of measurements and network topology changes). A new method is then developed for optimal meter placement, which is the choice of the optimal combination out of the selected candidate measurement sets in order to ensure the entire
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Palekar, Trishul Ajit. "Signal optimization at isolated intersections using pre-signals." Texas A&M University, 2006. http://hdl.handle.net/1969.1/4279.

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This research proposes a new signal operation strategy aimed at efficient utilization of green time by cutting down on the start up and response loss times. The idea is to have a "pre-signal" on each main approach a few hundred feet upstream of the intersection in addition to the main intersection signal, which is coordinated with the pre-signal. The offset between the main and pre-signal ensures that the majority of start up losses does not occur at the main signal. The benefits of the system under various traffic conditions were evaluated based on analysis of the queue discharge process and
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Eriksson, Daniel, and Axel Persson. "Energy Optimization of Scheduling and Packet Loss in Wireless Sensor Networks." Thesis, KTH, Skolan för elektro- och systemteknik (EES), 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-214699.

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We study the data aggregation of Wireless SensorNetworks (WSN). This is done by considering two problemformulations. The problems examine two different parts of thenetworks and their impact on its energy consumption. The firstproblem looks at the impact of packet loss and the secondproblem on the impact of network scheduling. The reason behindthis is that WSN usually operate on battery power and may beplaced in locations where they are hard to replace. Thus if itis possible to reduce the energy consumption of a WSN, thetotal lifespan of it will be increased. This led to the formulationof a NP-
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Hussein, Mohamed Gamar. "Optimization of PECVD boron-phosphorus doped silicon oxynitride for low-loss optical waveguides." Enschede : University of Twente [Host], 2007. http://doc.utwente.nl/57857.

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Books on the topic "Loss optimization"

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Eckenfelder, Donald J. Values-driven safety: Reengineering loss prevention using value inspired resource optimization. Government Institutes, 1996.

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Mago, Pedro J. Optimization of CCHP systems based on energy, economic and environmental considerations. Knovel, 2010.

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Mellis, Ian. Fat Loss Optimization. Lulu Press, Inc., 2009.

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Papier, Felix. Optimization of Rental Systems: Queuing Loss Theory for the Optimization of Cargo Vehicle Rental Systems. Springer Gabler, 2019.

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Red Light Therapy for Dummies: Anti-Aging, Fat Loss, Muscle Gain, Performance, and Brain Optimization. Independently Published, 2021.

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Advantages of Red Light Therapy: Anti-Aging, Fat Loss, Muscle Gain, Performance Enhancement, and Brain Optimization. Independently Published, 2021.

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Advanced Newest Red Light Therapy for Starter: Anti-Aging, Fat Loss, Muscle Gain, Performance, and Brain Optimization. Independently Published, 2022.

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Owens, Kimberly. All You Need to Know about Red Light Therapy: Use Red and near-Infrared Light Therapy for Anti-Aging, Weight Loss, Loss, and Brain Optimization. Independently Published, 2021.

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Adams, Jackie. All You Need to Know about Red Light Therapy: Use Red and near-Infrared Light Therapy for Anti-Aging, Weight Loss, Loss, and Brain Optimization. Independently Published, 2022.

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Cleaver, Joseph P., Alice Schmidt Kehaya, and Mikhail Kogan. Exercise, Frailty, and Functional Reserve: Concepts and Optimization. Oxford University Press, 2018. http://dx.doi.org/10.1093/med/9780190466268.003.0003.

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Regular exercise can increase the healthy lifespan of elderly patients. Despite this, most seniors are not getting enough exercise. This chapter summarizes the age-related declines in physical capacity, including loss of muscle power, decreased aerobic capacity (VO2max), sarcopenia, and increased adipose tissue, that can lead to inflammation and limitations of functional reserve. The concept of frailty is discussed. Clinicians are given practical techniques for evaluating risks in patients, providing an “exercise prescription” in an individually tailored manner, and measuring progress in their
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Book chapters on the topic "Loss optimization"

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Harjunkoski, Iiro, Ray Pörn, and Tapio Westerlund. "MINLP: Trim-Loss Problem." In Encyclopedia of Optimization. Springer Nature Switzerland, 2024. https://doi.org/10.1007/978-3-030-54621-2_387-1.

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Papier, Felix. "Convexity of Loss Probabilities." In Optimization of Rental Systems. Springer Fachmedien Wiesbaden, 2007. http://dx.doi.org/10.1007/978-3-658-24313-5_3.

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Hilgers, Michael. "Vehicle and Energy Loss." In Fuel Consumption and Consumption Optimization. Springer Berlin Heidelberg, 2023. http://dx.doi.org/10.1007/978-3-662-66449-0_2.

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Hilgers, Michael, and Wilfried Achenbach. "Vehicle and Energy Loss." In Fuel Consumption and Consumption Optimization. Springer Berlin Heidelberg, 2021. http://dx.doi.org/10.1007/978-3-662-60841-8_2.

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Marti, Kurt. "Stochastic Structural Optimization with Quadratic Loss Functions." In Stochastic Optimization Methods. Springer Berlin Heidelberg, 2015. http://dx.doi.org/10.1007/978-3-662-46214-0_7.

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Marti, Kurt. "Stochastic Structural Optimization with Quadratic Loss Functions." In Stochastic Optimization Methods. Springer International Publishing, 2024. http://dx.doi.org/10.1007/978-3-031-40059-9_12.

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Song, Yunlong. "Information-Loss-Bounded Policy Optimization." In Reinforcement Learning Algorithms: Analysis and Applications. Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-41188-6_8.

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Wilke, Daniel N. "Robust Optimization of Discontinuous Loss Functions." In Handbook of Formal Optimization. Springer Nature Singapore, 2024. http://dx.doi.org/10.1007/978-981-97-3820-5_1.

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Wilke, Daniel N. "Robust Optimization of Discontinuous Loss Functions." In Handbook of Formal Optimization. Springer Nature Singapore, 2024. http://dx.doi.org/10.1007/978-981-19-8851-6_1-1.

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Asperti, Andrea. "Variance Loss in Variational Autoencoders." In Machine Learning, Optimization, and Data Science. Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-64583-0_28.

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Conference papers on the topic "Loss optimization"

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Hongtong, Thak, Wuttikai Tammawan, Tatchakorn Thammapanya, Wiwat Tippachon, Theerawat Pussadee, and Phlearn Jansuya. "Analysis for Optimization Loss of Induction Heating." In 2024 International Conference on Materials and Energy: Energy in Electrical Engineering (ICOME-EE). IEEE, 2024. https://doi.org/10.1109/icome-ee64119.2024.10845403.

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Veretennikov, Nikolay Yu, and Yaroslav V. Skitsky. "Loss Optimization Approach in Flyback Transformer Windings." In 2024 IEEE 25th International Conference of Young Professionals in Electron Devices and Materials (EDM). IEEE, 2024. http://dx.doi.org/10.1109/edm61683.2024.10615169.

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Matsui, Atsuki, Ryoto Ishibashi, and Lin Meng. "YOLO Loss Optimization for Detecting Fruit Defects." In 2024 International Conference on Identification, Information and Knowledge in the Internet of Things (IIKI). IEEE, 2024. https://doi.org/10.1109/iiki65561.2024.00011.

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Hou, Yulin, Shiyi Shuai, and Yifei Xu. "Research on the loss optimization design of asynchronous motors." In 2024 3rd International Conference on Energy, Power and Electrical Technology (ICEPET). IEEE, 2024. http://dx.doi.org/10.1109/icepet61938.2024.10627312.

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Sahoo, P. B., Su Ma Nandar, Tan Tze Hian, and Chong Chia Yee. "Si -Photonics Waveguide Propagation Loss Improvement Through Process Optimization." In 2025 36th Annual SEMI Advanced Semiconductor Manufacturing Conference (ASMC). IEEE, 2025. https://doi.org/10.1109/asmc64512.2025.11010242.

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Halder, Tapas. "Loss Optimization of The High Frequency Solid State Transformer." In 2024 IEEE 11th Power India International Conference (PIICON). IEEE, 2024. https://doi.org/10.1109/piicon63519.2024.10995014.

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Nogueira, Vinicius, and Rogério Gonçalves dos Santos. "Head Loss Optimization." In Brazilian Congress of Thermal Sciences and Engineering. ABCM, 2018. http://dx.doi.org/10.26678/abcm.encit2018.cit18-0692.

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Emori, Kazuto, Toshihisa Shimizu, and Yoshio Bizen. "Discussion on design optimization of inductor loss focused on copper loss and iron loss." In 2013 1st International Future Energy Electronics Conference (IFEEC). IEEE, 2013. http://dx.doi.org/10.1109/ifeec.2013.6687510.

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Ranjbar, M., A. Vahdat, and G. Mori. "Complex loss optimization via dual decomposition." In 2012 IEEE Conference on Computer Vision and Pattern Recognition (CVPR). IEEE, 2012. http://dx.doi.org/10.1109/cvpr.2012.6247941.

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Hasan, Naimul, Ibraheem, and Yudhishthir Pandey. "Transmission Loss Allocation in Restructured Power system with optimization Loss Criterion." In 2018 2nd IEEE International Conference on Power Electronics, Intelligent Control and Energy Systems (ICPEICES). IEEE, 2018. http://dx.doi.org/10.1109/icpeices.2018.8897400.

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Reports on the topic "Loss optimization"

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Ruby, Jeffrey, Robert Fischer, Richard Massaro, et al. Optimization strategies for geospatial data on end-user devices. Engineer Research and Development Center (U.S.), 2024. http://dx.doi.org/10.21079/11681/49359.

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The ability to quickly disseminate geospatial data across all echelons, particularly those at the tactical edge, is critical to meeting threats described by the Multi-Domain Operations doctrine. The US Army Engineer Research and Development Center, Geospatial Research Laboratory (ERDC-GRL), is researching the optimization of the formats, data models, file sizes, and quality of geospatial products to be exploited by end-user devices (EUDs). This report describes a processing methodology comprising custom software and open-source tools to optimize Army Geospatial Enterprise Standard Sharable Geo
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Ruby, Jeffrey, Robert Fischer, Richard Massaro, et al. Optimization strategies for geospatial data on end-user devices. Engineer Research and Development Center (U.S.), 2024. http://dx.doi.org/10.21079/11681/49366.

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The ability to quickly disseminate geospatial data across all echelons, particularly those at the tactical edge, is critical to meeting threats described by the Multi-Domain Operations doctrine. The US Army Engineer Research and Development Center, Geospatial Research Laboratory (ERDC-GRL), is researching the optimization of the formats, data models, file sizes, and quality of geospatial products to be exploited by end-user devices (EUDs). This report describes a processing methodology comprising custom software and open-source tools to optimize Army Geospatial Enterprise Standard Sharable Geo
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Filipiak, Katarzyna, Dietrich von Rosen, Martin Singull, and Wojciech Rejchel. Estimation under inequality constraints in univariate and multivariate linear models. Linköping University Electronic Press, 2024. http://dx.doi.org/10.3384/lith-mat-r-2024-01.

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In this paper least squares and maximum likelihood estimates under univariate and multivariate linear models with a priori information related to maximum effects in the models are determined. Both loss functions (the least squares and negative log-likelihood) and the constraints are convex, so the convex optimization theory can be utilized to obtain estimates, which in this paper are called Safety belt estimates. In particular, the complementary slackness condition, common in convex optimization, implies two alternative types of solutions, strongly dependent on the data and the restriction. It
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DiDomizio, Matthew, and Jonathan Butta. Measurement of Heat Transfer and Fire Damage Patterns on Walls for Fire Model Validation. UL Research Institutes, 2024. http://dx.doi.org/10.54206/102376/hnkr9109.

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Fire models are presently employed by fire investigators to make predictions of fire dynamics within structures. Predictions include the evolution of gas temperatures and velocities, smoke movement, fire growth and spread, and thermal exposures to surrounding objects, such as walls. Heat flux varies spatially over exposed walls based on the complex thermal interactions within the fire environment, and is the driving factor for thermally induced fire damage. A fire model predicts the temperature and heat transfer through walls based on field predictions, such as radiative and convective heat fl
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Zhou, F., Y. Nosochkov, J. C. Sheppard, and W. Liu. Collimation Optimizations, Capture Efficiency, and Primary-beam Power Loss in the ILC Positron Source Transport. Office of Scientific and Technical Information (OSTI), 2007. http://dx.doi.org/10.2172/917271.

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Li, Y., D. Eastlake, L. Dunbar, R. Perlman, and M. Umair. Transparent Interconnection of Lots of Links (TRILL): ARP and Neighbor Discovery (ND) Optimization. RFC Editor, 2018. http://dx.doi.org/10.17487/rfc8302.

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Tsur, Yacov, David Zilberman, Uri Shani, Amos Zemel, and David Sunding. Dynamic intraseasonal irrigation management under water scarcity, water quality, irrigation technology and environmental constraints. United States Department of Agriculture, 2007. http://dx.doi.org/10.32747/2007.7696507.bard.

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In this project we studied optimal use and adoption of sophisticated irrigation technologies. The stated objectives in the original proposal were to develop a conceptual framework for analyzing intra-season timing of water application rates with implications for crop and irrigation technology selection. We proposed to base the analysis on an intra-seasonal, dynamic, agro-economic model of plants' water demand, paying special attention to contamination of groundwater and soil in intensively cultivated areas that increasingly rely on water of lesser quality. The framework developed in the projec
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Petzke, Jonas, Dennis Kleinschmidt, and Florian Brüning. Simulative approach for predicting the heating behavior of elastomers in the solid-state microwave heating process. Universidad de los Andes, 2024. https://doi.org/10.51573/andes.pps39.gs.ms.2.

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The increasing demand for energy efficient vulcanization of rubber extrusions requires the optimization and further development of existing processes. Microwave vulcanization allows the energy required for this process to be coupled directly into the material via dielectric losses. Microwave heating requires the polarity of the rubber so that the electromagnetic wave can cause the polar components of the material to vibrate. These vibrations cause internal friction, resulting in an increase in the temperature of the rubber compound. In this research project, microwaves were used to heat a rubb
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Urban, Angela, Susannah Davidson, and Allison Young. Dining facility w/hole-building evaluation to reduce solid waste : opportunities and best practices for optimization and management of food waste. Engineer Research and Development Center (U.S.), 2023. http://dx.doi.org/10.21079/11681/47560.

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On military installations, an average of 1.2 pounds in food waste is disposed per person per day, accounting for 68% of dining facility (DFAC) refuse and 46% of the total installation refuse stream, making food waste the heaviest portion of installation solid waste. At a single installation, this can contribute up to 1.5 million dollars lost yearly from food waste alone. Department of Defense Instruction (DoDI) 4715.23 (DoD 2016) establishes policy and prescribes procedures to implement waste management through waste prevention and recycling. The US Army Installation Management Commands (IMCOM
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Einarsson, Rasmus. Nitrogen in the food system. TABLE, 2024. http://dx.doi.org/10.56661/2fa45626.

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Nitrogen (N) plays a dual role in the agri-food system: it is an essential nutrient for all life forms, yet also an environmental pollutant causing a range of environmental and human health impacts. As the plant nutrient needed in greatest quantities, and as a building block of proteins and other biomolecules, N is a necessary part of all life. In the last century, an enormous increase of N turnover in the agri-food system has enabled increasing per-capita food supply for a growing world population, but as an unintended side effect, N pollution has increased to levels widely agreed in science
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