Relevant bibliographies by topics / Liquid Time Constant Networks

Academic literature on the topic 'Liquid Time Constant Networks'

Author: Grafiati
Published: 10 December 2022
Last updated: 29 January 2023

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Journal articles on the topic "Liquid Time Constant Networks"

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Hasani, Ramin, Mathias Lechner, Alexander Amini, Daniela Rus, and Radu Grosu. "Liquid Time-constant Networks." Proceedings of the AAAI Conference on Artificial Intelligence 35, no. 9 (May 18, 2021): 7657–66. http://dx.doi.org/10.1609/aaai.v35i9.16936.

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We introduce a new class of time-continuous recurrent neural network models. Instead of declaring a learning system's dynamics by implicit nonlinearities, we construct networks of linear first-order dynamical systems modulated via nonlinear interlinked gates. The resulting models represent dynamical systems with varying (i.e., liquid) time-constants coupled to their hidden state, with outputs being computed by numerical differential equation solvers. These neural networks exhibit stable and bounded behavior, yield superior expressivity within the family of neural ordinary differential equations, and give rise to improved performance on time-series prediction tasks. To demonstrate these properties, we first take a theoretical approach to find bounds over their dynamics, and compute their expressive power by the trajectory length measure in a latent trajectory space. We then conduct a series of time-series prediction experiments to manifest the approximation capability of Liquid Time-Constant Networks (LTCs) compared to classical and modern RNNs.
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Hasani, Ramin, Mathias Lechner, Alexander Amini, Lucas Liebenwein, Aaron Ray, Max Tschaikowski, Gerald Teschl, and Daniela Rus. "Closed-form continuous-time neural networks." Nature Machine Intelligence 4, no. 11 (November 15, 2022): 992–1003. http://dx.doi.org/10.1038/s42256-022-00556-7.

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AbstractContinuous-time neural networks are a class of machine learning systems that can tackle representation learning on spatiotemporal decision-making tasks. These models are typically represented by continuous differential equations. However, their expressive power when they are deployed on computers is bottlenecked by numerical differential equation solvers. This limitation has notably slowed down the scaling and understanding of numerous natural physical phenomena such as the dynamics of nervous systems. Ideally, we would circumvent this bottleneck by solving the given dynamical system in closed form. This is known to be intractable in general. Here, we show that it is possible to closely approximate the interaction between neurons and synapses—the building blocks of natural and artificial neural networks—constructed by liquid time-constant networks efficiently in closed form. To this end, we compute a tightly bounded approximation of the solution of an integral appearing in liquid time-constant dynamics that has had no known closed-form solution so far. This closed-form solution impacts the design of continuous-time and continuous-depth neural models. For instance, since time appears explicitly in closed form, the formulation relaxes the need for complex numerical solvers. Consequently, we obtain models that are between one and five orders of magnitude faster in training and inference compared with differential equation-based counterparts. More importantly, in contrast to ordinary differential equation-based continuous networks, closed-form networks can scale remarkably well compared with other deep learning instances. Lastly, as these models are derived from liquid networks, they show good performance in time-series modelling compared with advanced recurrent neural network models.
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Gupta, Anunay, Anindya Gupta, Apoorv Bansal, and Madan Mohan Tripathi. "Solar Power Prediction using LTC Models." International Journal of Electrical and Electronics Research 10, no. 3 (September 30, 2022): 475–80. http://dx.doi.org/10.37391/ijeer.100312.

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Renewable energy production has been increasing at a tremendous rate in the past decades. This increase in production has led to various benefits such as low cost of energy production and making energy production independent of fossil fuels. However, in order to fully reap the benefits of renewable energy and produce energy in an optimum manner, it is essential that we forecast energy production. Historically deep learning-based techniques have been successful in accurately forecasting solar energy production. In this paper we develop an ensemble model that utilizes ordinary differential based neural networks (Liquid Time constant Networks and Recurrent Neural networks) to forecast solar power production 24 hours ahead. Our ensemble is able to achieve superior result with MAPE of 5.70% and an MAE of 1.07 MW.
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Li, Yannanqi, Zhiyong Yang, Ran Chen, Lingchao Mo, Juanli Li, Minggang Hu, and Shin-Tson Wu. "Submillisecond-Response Polymer Network Liquid Crystal Phase Modulators." Polymers 12, no. 12 (November 30, 2020): 2862. http://dx.doi.org/10.3390/polym12122862.

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A submillisecond-response and light scattering-free polymer-network liquid crystal (PNLC) for infrared spatial light modulators is demonstrated. Our new liquid crystal host exhibits a higher birefringence, comparable dielectric anisotropy, and slightly lower visco-elastic constant than a commonly employed commercial material, HTG-135200. Moreover, the electro-optical performance of our PNLCs with different monomer concentrations, cell gaps, and liquid crystal (LC) hosts is compared and discussed from four aspects: operating voltage, hysteresis, relaxation time, and light scattering loss. The temperature effect on hysteresis is also analyzed. Potential applications of PNLCs for laser beam steering and spatial light modulators especially in the infrared region are foreseeable.
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Bouvier, J. M., and M. Gelus. "Diffusion of Heavy Oil in a Swelling Elastomer." Rubber Chemistry and Technology 59, no. 2 (May 1, 1986): 233–40. http://dx.doi.org/10.5254/1.3538196.

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Abstract The swelling of SBR by an aromatic oil has been experimentally studied at temperatures ranging from ambient to 200°C with thermally stable networks. A model based on Fick's law was developed, and the change of geometry of the elastomer sample was taken into account. The proposed approach is global or macroscopic, and a constant diffusion coefficient has been defined. The diffusion number, ND, defined by two characteristics of a solvent-polymer system, tf the swelling time and tD the diffusion time, represents an important result for engineering applications; it allows prediction of the behavior of amorphous elastomers in contact with a diffusing organic liquid.
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Shumate, Justin, Pierre Baillargeon, Timothy P. Spicer, and Louis Scampavia. "IoT for Real-Time Measurement of High-Throughput Liquid Dispensing in Laboratory Environments." SLAS TECHNOLOGY: Translating Life Sciences Innovation 23, no. 5 (April 12, 2018): 440–47. http://dx.doi.org/10.1177/2472630318769454.

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Critical to maintaining quality control in high-throughput screening is the need for constant monitoring of liquid-dispensing fidelity. Traditional methods involve operator intervention with gravimetric analysis to monitor the gross accuracy of full plate dispenses, visual verification of contents, or dedicated weigh stations on screening platforms that introduce potential bottlenecks and increase the plate-processing cycle time. We present a unique solution using open-source hardware, software, and 3D printing to automate dispenser accuracy determination by providing real-time dispense weight measurements via a network-connected precision balance. This system uses an Arduino microcontroller to connect a precision balance to a local network. By integrating the precision balance as an Internet of Things (IoT) device, it gains the ability to provide real-time gravimetric summaries of dispensing, generate timely alerts when problems are detected, and capture historical dispensing data for future analysis. All collected data can then be accessed via a web interface for reviewing alerts and dispensing information in real time or remotely for timely intervention of dispense errors. The development of this system also leveraged 3D printing to rapidly prototype sensor brackets, mounting solutions, and component enclosures.
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Maximean, Doina Manaila, Octavian Danila, Pedro L. Almeida, and Constantin Paul Ganea. "Electrical properties of a liquid crystal dispersed in an electrospun cellulose acetate network." Beilstein Journal of Nanotechnology 9 (January 15, 2018): 155–63. http://dx.doi.org/10.3762/bjnano.9.18.

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Electro-optical devices that work in a similar fashion as PDLCs (polymer-dispersed liquid crystals), produced from cellulose acetate (CA) electrospun fibers deposited onto indium tin oxide coated glass and a nematic liquid crystal (E7), were studied. CA and the CA/liquid crystal composite were characterized by multiple investigation techniques, such as polarized optical microscopy, dielectric spectroscopy and impedance measurements. Dielectric constant and electric energy loss were studied as a function of frequency and temperature. The activation energy was evaluated and the relaxation time was obtained by fitting the spectra of the dielectric loss with the Havriliak–Negami functions. To determine the electrical characteristics of the studied samples, impedance measurements results were treated using the Cole–Cole diagram and the three-element equivalent model.
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Kalisiak, Michał, and Wojciech Wiatr. "Complete Meniscus Removal Method for Broadband Liquid Characterization in a Semi-Open Coaxial Test Cell." Sensors 19, no. 9 (May 6, 2019): 2092. http://dx.doi.org/10.3390/s19092092.

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We present a new technique for broadband liquid characterization using a semi-open, vertically oriented test cell that is measured with a calibrated vector network analyzer in three states: the empty one and filled with two different volumes of the liquid under test. Using the measurements, we de-embed a transfer matrix representing a volume increment of the liquid sample and determine its column height with a novel closed-form formula. Thanks to the de-embedding, the method enables one, for the first time, to completely remove effects caused by a reproducible meniscus forming the top surface of a liquid tested in the cell and determine not only the propagation constant, but also characteristic impedance of the liquid sample, from which its permittivity and permeability are calculated. The results are highly consistent, because all the measurements are performed without disassembling the cell. We validate experimental results of the meniscus removal method by comparing them with reference data and outcomes of the Nicolson–Ross–Weir method.
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Promhuad, Khwanchat, and Wirasak Smitthipong. "Effect of Stabilizer States (Solid Vs Liquid) on Properties of Stabilized Natural Rubbers." Polymers 12, no. 4 (March 27, 2020): 741. http://dx.doi.org/10.3390/polym12040741.

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The main objective of this work is to study the effect of hydroxylamine sulfate or stabilizer states (solid vs liquid) on the storage hardening of natural rubber (NR). Several types of natural rubber samples were prepared: unstabilized NR samples and stabilized NR samples: (i) dry NR with 0.2 and 2.0 parts per hundred rubber (phr) of dry hydroxylamine sulfate, and (ii) natural latex with 0.2 and 2.0 phr of liquid hydroxylamine sulfate. The samples were characterized immediately (time 0) and after 12 weeks of storage at room temperature, respectively. We found that the Mooney viscosity, gel content, and Wallace plasticity of NR without a stabilizer increases with storage hardening for 12 weeks. However, two types of stabilized NR samples represent constant values of those three parameters, because hydroxylamine sulfate inhibits network and gel formation in NR. Interestingly, the mixing states (solid vs liquid) between natural rubber and the stabilizer affect the properties of stabilized NR. This could be explained by the better dispersion and homogeneous nature of liquid stabilizers in natural latex (liquid state), and thus the higher loading of the stabilizer in the liquid state. This is important, as the stabilization of NR properties as a function of time is required by rubber industry. This study is a utilization model from theory to application.
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Wang, Xian, Zhengxiang Song, Kun Yang, Xuyang Yin, Yingsan Geng, and Jianhua Wang. "State of Charge Estimation for Lithium-Bismuth Liquid Metal Batteries." Energies 12, no. 1 (January 7, 2019): 183. http://dx.doi.org/10.3390/en12010183.

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Lithium-bismuth liquid metal batteries have much potential for stationary energy storage applications, with characteristics such as a large capacity, high energy density, low cost, long life-span and an ability for high current charge and discharge. However, there are no publications on battery management systems or state-of-charge (SoC) estimation methods, designed specifically for these devices. In this paper, we introduce the properties of lithium-bismuth liquid metal batteries. In analyzing the difficulties of traditional SoC estimation techniques for these devices, we establish an equivalent circuit network model of a battery and evaluate three SoC estimation algorithms (the extended Kalman filter, the unscented Kalman filter and the particle filter), using constant current discharge, pulse discharge and hybrid pulse (containing charging and discharging processes) profiles. The results of experiments performed using the equivalent circuit battery model show that the unscented Kalman filter gives the most robust and accurate performance, with the least convergence time and an acceptable computation time, especially in hybrid pulse current tests. The time spent on one estimation with the three algorithms are 0.26 ms, 0.5 ms and 1.5 ms.
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Dissertations / Theses on the topic "Liquid Time Constant Networks"

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Carnell, Andrew Robert. "Aspects of learning within networks of spiking neurons." Thesis, University of Bath, 2008. https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.512264.

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Spiking neural networks have, in recent years, become a popular tool for investigating the properties and computational performance of large massively connected networks of neurons. Equally as interesting is the investigation of the potential computational power of individual spiking neurons. An overview is provided of current and relevant research into the Liquid Sate Machine, biologically inspired artificial STDP learning mechanisms and the investigation of aspects of the computational power of artificial, recurrent networks of spiking neurons. First, it is shown that, using simple structures of spiking Leaky Integrate and Fire (LIF) neurons, a network n(P), can be built to perform any program P that can be performed by a general parallel programming language. Next, a form of STDP learning with normalisation is developed, referred to as STDP + N learning. The effects of applying this STDP + N learning within recurrently connected networks of neurons is then investigated. It is shown experimentally that, in very specific circumstances Anti-Hebbian and Hebbian STDP learning may be considered to be approximately equivalent processes. A metric is then developed that can be used to measure the distance between any two spike trains. The metric is then used, along with the STDP + N learning, in an experiment to examine the capacity of a single spiking neuron that receives multiple input spike trains, to simultaneously learn many temporally precise Input/Output spike train associations. The STDP +N learning is further modified for use in recurrent networks of spiking neurons, to give the STDP + NType2 learning methodology. An experiment is devised which demonstrates that the Type 2 method of applying learning to the synapses of a recurrent network — effectively a randomly shifting locality of learning — can enable the network to learn firing patterns that the typical application of learning is unable to learn. The resulting networks could, in theory, be used to create to simple structures discussed in the first chapter of original work.
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Perchiazzi, Gaetano. "Artificial Neural Networks (ANN) in the Assessment of Respiratory Mechanics." Doctoral thesis, Uppsala : Acta Universitatis Upsaliensis : Univ.-bibl. [distributör], 2004. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-4665.

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Seuret, Alexandre, Dimos V. Dimarogonas, and Karl Henrik Johansson. "Consensus under communication delays." KTH, Reglerteknik, 2008. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-28520.

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This paper deals with the consensus problem under communication network inducing delays. It is well-known that introducing a delay leads in general to a reduction of the performance or to instability due to the fact that timedelay systems are infinite dimensional. For instance, the set of initial conditions of a time-delay system is not a vector but a function taken in an interval. Therefore, investigating the effect of time-delays in the consensus problem is an important issue. In the present paper, we assume that each agent receives instantaneously its own state information but receives the state information from its neighbors after a constant delay. Two stability criteria are provided based on the frequency approach and on Lyapunov-Krasovskii techniques given in terms of LMI. An analytic expression of the consensus equilibrium which depends on the delay and on the initial conditions taken in an interval is derived. The efficiency of the method is tested for different network communication schemes.

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Tsai, Tung-Lin, and 蔡東霖. "Repacking and Borrowing-Based Constant-Time Resource Scheduling for IEEE 802.16j Multihop Relay Networks." Thesis, 2009. http://ndltd.ncl.edu.tw/handle/05041901600534392365.

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碩士
國立清華大學
資訊工程學系
97
Multihop relay (MR) technology is one of the most promising technologies that provide performance enhancement to the existing network systems. To achieve the maximal system performance, most current research allocates resources in a dynamic manner. However, in MR networks, the issues of path selection and spatial reuse will massively increase the complexity of resource scheduling. As a result, the majority of dynamic scheduling schemes might be not applicable in practical implementation due to high computation complexity. In this paper, to reduce the scheduling complexity while achieving near-optimal system throughput, we propose a constant-time repacking and borrowing-based resource scheduling (RBRS) algorithm for IEEE 802.16j MR networks. In the repacking phase of RBRS, the connection which served with high-cost path can be handed off to low-cost path and thus increase the number of available resources. In the borrowing phase, the overloaded cells are capable of borrowing resources from the under-loaded cells and thus the resource utilization can be further improved. Since both the repacking and borrowing processes are executed only with computation overhead of the selection operation, RBRS can make each scheduling decision in constant time. Simulation models are developed to investigate the performance of RBRS. The simulation results indicate that RBRS is at least 8.91 times faster than the state-of-the-art dynamic scheduling scheme while yielding near-optimal throughput. Even in the asymmetric environments, RBRS strikes an excellent balance between the system throughput and scheduling computation time.
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Books on the topic "Liquid Time Constant Networks"

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ZnO bao mo zhi bei ji qi guang, dian xing neng yan jiu. Shanghai Shi: Shanghai da xue chu ban she, 2010.

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Allen, Michael P., and Dominic J. Tildesley. Inhomogeneous fluids. Oxford University Press, 2017. http://dx.doi.org/10.1093/oso/9780198803195.003.0014.

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In this chapter, the special techniques needed to simulate and calculate properties for inhomogeneous systems are presented. The estimation of surface properties, such as the interfacial tension, may be accomplished by a variety of methods, including the calculation of the stress tensor profiles, the change in the potential energy on scaling the surface area at constant volume, the observation of equilibrium capillary wave fluctuations, or direct free energy measurement by cleaving. The structure within the interface is also of interest, and ways of quantifying this are described. Practical issues such as system size, preparation of a two-phase system, and equilibration time, are discussed. Special application areas, such as liquid drops, fluid membranes, and liquid crystals, are described.
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Zaritt, Saul Noam. Jewish American Writing and World Literature. Oxford University Press, 2020. http://dx.doi.org/10.1093/oso/9780198863717.001.0001.

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Jewish American Writing and World Literature studies Jewish American writers’ relationships with the idea of world literature—how they place themselves within its boundaries, outside its purview, or, most often, in constant motion across and beyond its maps and networks. Writers such as Sholem Asch, Jacob Glatstein, Isaac Bashevis Singer, Anna Margolin, Saul Bellow, and Grace Paley all responded to a demand to write beyond local Jewish and American audiences and toward the world, as a global market and as a transnational ideal. At the same time, their work is deeply informed by an intimate connection to Yiddish, a Jewish vernacular with its own global network and institutional ambitions. This book tracks the attempts and failures, through translation, to find a home for Jewish vernacularity in the institution of world literature. Beyond fame and global circulation, world literature holds up the promise of legibility, in which a threatened origin becomes the site for redemptive literary creativity. But this promise inevitably remains unfulfilled, as writers struggle to balance potential universal achievements with untranslatable realities, rendering impossible any complete arrival in the US and in the world. The exploration of the translational uncertainty of Jewish American writing joins postcolonial critiques of US and world literature and challenges Eurocentric and Anglo-American paradigms of literary study. In bringing into conversation the fields of Yiddish studies, American Studies, and world literature theory, the book proposes a new approach to the study of modern Jewish literatures and their implication within global empires of culture.
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Book chapters on the topic "Liquid Time Constant Networks"

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Zhang, Ziye, Zhen Wang, Jian Chen, and Chong Lin. "Stability Criterion for CVNNs with Constant Delay." In Complex-Valued Neural Networks Systems with Time Delay, 27–36. Singapore: Springer Nature Singapore, 2022. http://dx.doi.org/10.1007/978-981-19-5450-4_2.

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Zhang, Ziye, Zhen Wang, Jian Chen, and Chong Lin. "Further Stability Analysis for CVNNs with Constant Delay." In Complex-Valued Neural Networks Systems with Time Delay, 37–52. Singapore: Springer Nature Singapore, 2022. http://dx.doi.org/10.1007/978-981-19-5450-4_3.

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Zhang, Ziye, Zhen Wang, Jian Chen, and Chong Lin. "Finite-Time Stability Analysis for CVBAMNNs with Constant Delay." In Complex-Valued Neural Networks Systems with Time Delay, 79–94. Singapore: Springer Nature Singapore, 2022. http://dx.doi.org/10.1007/978-981-19-5450-4_5.

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Miller, Robert, and Phil Maguire. "GeoTree: A Data Structure for Constant Time Geospatial Search Enabling a Real-Time Property Index." In Lecture Notes in Networks and Systems, 152–65. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-80126-7_12.

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Sanders, Peter, and Dominik Schultes. "Robust, almost constant time shortest-path queries in road networks." In DIMACS Series in Discrete Mathematics and Theoretical Computer Science, 193–218. Providence, Rhode Island: American Mathematical Society, 2009. http://dx.doi.org/10.1090/dimacs/074/08.

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Hore, Ayan, Pratik Jain, and Debashis Chakraborty. "An Efficient Speech Compression Technique in Time Domain with Nearly Constant Compression." In Lecture Notes in Networks and Systems, 15–22. Singapore: Springer Singapore, 2018. http://dx.doi.org/10.1007/978-981-10-8204-7_2.

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Abichar, Zakhia G., and J. Morris Chang. "CONTI: Constant-Time Contention Resolution for WLAN Access." In NETWORKING 2005. Networking Technologies, Services, and Protocols; Performance of Computer and Communication Networks; Mobile and Wireless Communications Systems, 358–69. Berlin, Heidelberg: Springer Berlin Heidelberg, 2005. http://dx.doi.org/10.1007/11422778_29.

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Chen, Bao-Xing, Ji-Xiang Meng, and Wen-Jun Xiao. "A Constant Time Optimal Routing Algorithm for Undirected Double-Loop Networks." In Lecture Notes in Computer Science, 308–16. Berlin, Heidelberg: Springer Berlin Heidelberg, 2005. http://dx.doi.org/10.1007/11599463_31.

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Bast, Holger, Stefan Funke, Domagoj Matijevic, Peter Sanders, and Dominik Schultes. "In Transit to Constant Time Shortest-Path Queries in Road Networks." In 2007 Proceedings of the Ninth Workshop on Algorithm Engineering and Experiments (ALENEX), 46–59. Philadelphia, PA: Society for Industrial and Applied Mathematics, 2007. http://dx.doi.org/10.1137/1.9781611972870.5.

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Park, Ju H., Tae H. Lee, Yajuan Liu, and Jun Chen. "State Estimation of Genetic Regulatory Networks with Leakage, Constant, and Distributed Time-Delays." In Dynamic Systems with Time Delays: Stability and Control, 295–311. Singapore: Springer Singapore, 2019. http://dx.doi.org/10.1007/978-981-13-9254-2_13.

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Conference papers on the topic "Liquid Time Constant Networks"

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Yin, Hao, Yaohai Zhou, Liu Cao, and Yifei Xu. "Channel Prediction with Liquid Time-Constant Networks: An Online and Adaptive Approach." In 2021 IEEE 94th Vehicular Technology Conference (VTC2021-Fall). IEEE, 2021. http://dx.doi.org/10.1109/vtc2021-fall52928.2021.9625323.

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Shang, Hongcheng, and Bin-Jie Hu. "CALNet: LiDAR-Camera Online Calibration With Channel Attention and Liquid Time-Constant Network." In 2022 26th International Conference on Pattern Recognition (ICPR). IEEE, 2022. http://dx.doi.org/10.1109/icpr56361.2022.9956145.

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Peraza, Jesús Enrique, Raul Payri, Jaime Gimeno, and Tim Bazyn. "Spray/wall interaction analysis on an ECN single-hole injector at diesel-like conditions through Schlieren visualization." In ILASS2017 - 28th European Conference on Liquid Atomization and Spray Systems. Valencia: Universitat Politècnica València, 2017. http://dx.doi.org/10.4995/ilass2017.2017.4709.

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To continuously improve CFD models which simulate spray evolution, breakup and evaporation mechanisms, it is helpful to validate them with results obtained by experimental research. In the present study, a mono-orifice target nozzle from Engine Combustion Network, referred to as Spray D, was investigated at conditions of spray-wall interaction, which actually is a real situation in internal combustion engines that is not frequently analyzed by visualization. A Photron SA-X2 high-speed camera was employed to record the vapor phase development of the spray in an inert atmosphere using a Schlieren imaging single-pass setup. The experiments show that the spreading of the spray along the wall has a behavior fairly similar to penetration at free-jet situations, especially regarding to its susceptibility to the operating conditions and its proportionality to the square root of time once the spray reaches a steady regime interacting with the wall. Furthermore, the spray film thickness was measured at three distances from the spray-wall impact point during the injection event, thereby characterizing that parameter both spatially and temporally. The tests were carried out in a constant pressure-flow facility able to reproduce pressure and temperature conditions, similar to those seen into a diesel engine. In order to observe the behavior of the spray colliding with a wall within this test rig, a system capable to being fitted into it and to holding a fused quartz wall at different injector tip-wall distances and impingement angle configurations, was designed and employed.DOI: http://dx.doi.org/10.4995/ILASS2017.2017.4709
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Yiotis, A. G., A. K. Stubos, A. G. Boudouvis, and Y. C. Yortsos. "A Pore Network Model for Drying Processes in Porous Media." In ASME 2001 International Mechanical Engineering Congress and Exposition. American Society of Mechanical Engineers, 2001. http://dx.doi.org/10.1115/imece2001/htd-24155.

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Abstract A pore network model for the drying of capillary porous media is presented in this work. The model accounts for various processes at the pore scale including evaporation of a volatile liquid, mass transfer of the vapors by advection and diffusion in the gas phase and viscous flow in the liquid and gas phases. Both viscous and capillary forces at the liquid menisci in pore throats are also modeled. We consider isothermal drying in a rectilinear horizontal geometry, with no flow conditions in all but one boundary, at which a purge gas is injected at a constant rate. Drying rates, phase distribution and concentration patterns are reported as a function of time and the gas flow rate. We also refer to the evolution of trapped liquid clusters.
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Kempitiya, Asantha, Mona M. Hella, and Diana A. Borca-Tasciuc. "Modeling of Kinetic to Electrical Energy Conversion via Capacitive MEMS With Switchable Dielectric." In ASME 2008 International Mechanical Engineering Congress and Exposition. ASMEDC, 2008. http://dx.doi.org/10.1115/imece2008-66794.

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Wireless distributed micro-sensor systems have numerous applications, from equipment diagnostic and control to real time biomedical monitoring. A major obstacle in developing autonomous micro-sensor networks is the need for local, autonomous electric power supply, since using a battery is often not a viable solution. This work investigates a novel micro-power generator converting ambient vibrations to electrical energy via electrostatic transduction employing a comb-like variable capacitor, with a switchable dielectric constant. The micro-generator is designed to operate in an inplane, gap closing, and charge constrained configuration. Enhanced power levels are obtained by pulling a high dielectric constant liquid between the capacitor gaps via electrochemical force effect at maximum capacitance position. The effects of squeeze film damping and variable electrostatic force induced by the varying spatial distribution of dielectric medium are taken into account. In this configuration the microgenerator exhibits high quality factors, thus providing an output power higher of approximately 168 μW.
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Ito, Hiro. "Constant-Time Algorithms for Complex Networks." In 2016 3rd Asia-Pacific World Congress on Computer Science and Engineering (APWC on CSE). IEEE, 2016. http://dx.doi.org/10.1109/apwc-on-cse.2016.014.

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Dubhashi, D., C. Johansson, O. Häggström, A. Panconesi, and M. Sozio. "Irrigating ad hoc networks in constant time." In the 17th annual ACM symposium. New York, New York, USA: ACM Press, 2005. http://dx.doi.org/10.1145/1073970.1073986.

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Liu, Xiwei, and Han Zhang. "Fixed Time Synchronization of Complex Networks with Constant Time Delay." In 2020 35th Youth Academic Annual Conference of Chinese Association of Automation (YAC). IEEE, 2020. http://dx.doi.org/10.1109/yac51587.2020.9337496.

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Mun, Jiwon, Jaehyung Ju, Byoung-Gwan Yun, Byung-Moon Chang, and Doo-Man Kim. "A Numerical Study of a Molten Aluminum for Investment Casting of 3D Cellular Metals." In ASME 2013 International Mechanical Engineering Congress and Exposition. American Society of Mechanical Engineers, 2013. http://dx.doi.org/10.1115/imece2013-62847.

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Abstract:
Investment casting processes are influenced by a variety of parameters. Many researches considering viscosity as a constant have been conducted up to this point. In particular, however, viscosity with temperature change has not been much accounted for solidification and heat transfer simulation of molten metal in the investment casting process. In addition, analysis of behavior of metal flow as well as air gap problems for complex network structures have not been investigated much. The aim of this study is to build transient metal flow and velocity profile models considering temperature dependent viscosity in investment casting processes of cellular structures. In this study, a Computational Fluid Dynamics (CFD) modeling tool was used for metal flow and velocity profile in investment casting processing using User Defined Function (UDF) for temperature dependent viscosity. The results of the metal flow and velocity profile inside of the simple cylindrical geometry are represented. It is shown that for the validation of the numerical simulation, the velocity profile between analytical and numerical approaches showed very good agreement. Analytical approaches showed that velocity was reduced with the increase in viscosity, which is applied as a function of temperature. In particular, rapid decreasing in velocity was shown from under the melting temperature of the molten metal. There was no movement on metal flow at the room temperature. Numerical approaches showed that the liquid metal began to be solidified from the wall surface inside of the mold. For the same simulation time, it was shown that the metal flow in a cylinder that has 1mm diameter showed better fluidity rather than that of the cylinder that has 2mm diameter due to the increase in adhesion between liquid metal and the surface of the mold and surface tension between molten metal and air. The effective diameter by solidification is decreased with the time change.
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10

Alomair, Basel, Andrew Clark, Jorge Cuellar, and Radha Poovendran. "Scalable RFID systems: a privacy-preserving protocol with constant-time identification." In Networks (DSN). IEEE, 2010. http://dx.doi.org/10.1109/dsn.2010.5545008.

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