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Parallelization of structured, hierarchical adaptive mesh refinement algorithms

Computing and Visualization in Science 2000年第3期3卷 147-157页

作者： Rendleman, Charles A. Beckner, Vincent E. Lijewski, Mike Crutchfield, William Bell, John B. Lawrence Berkeley National Laboratory Berkeley CA 94720 United States

We describe an approach to parallelization of structured adaptive mesh refinement algorithms. This type of adaptive methodology is based on the use of local grids superimposed on a coarse grid to achieve sufficient resolution in the solution. The key elements of the approach to parallelization are a dynamic load-balancing technique to distribute work to processors and a software methodology for managing data distribution and communications. The methodology is based on a message-passing model that exploits the coarsegrained parallelism inherent in the algorithms. The approach is illustrated for an adaptive algorithm for hyperbolic systems of conservation laws in three space dimensions. A numerical example computing the interaction of a shock with a helium bubble is *** give timings to illustrate the performance of the method. © 2000 Springer-Verlag.

关键词： adaptive algorithms

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Stable Matching with Interviews

arXiv

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arXiv 2025年

作者： Ashlagi, Itai Chen, Jiale Roghani, Mohammad Saberi, Amin Stanford University United States

In several two-sided markets, including labor and dating, agents typically have limited information about their preferences prior to mutual interactions. This issue can result in matching frictions, as arising in the labor market for medical residencies, where high application rates are followed by a large number of interviews. Yet, the extensive literature on two-sided matching primarily focuses on models where agents know their preferences, leaving the interactions necessary for preference discovery largely overlooked. This paper studies this problem using an algorithmic approach, extending Gale-Shapley's deferred acceptance to this context. Two algorithms are proposed. The first is an adaptive algorithm that expands upon Gale-Shapley's deferred acceptance by incorporating interviews between applicants and positions. Similar to deferred acceptance, one side sequentially proposes to the other. However, the order of proposals is carefully chosen to ensure an interim stable matching is found. Furthermore, with high probability, the number of interviews conducted by each applicant or position is limited to O(log2 n). In many seasonal markets, interactions occur more simultaneously, consisting of an initial interview phase followed by a clearing stage. We present a non-adaptive algorithm for generating a single stage set of in tiered random markets. The algorithm finds an interim stable matching in such markets while assigning no more than O(log3 n) interviews to each applicant or position. © 2025, CC BY.

关键词： adaptive algorithms

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adaptive dead reckoning algorithms for Distributed Interactive Simulation

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International Journal of Simulation: Systems, Science and Technology 2000年第1-2期1卷 21-34页

作者： Lee, Bu-Sung Cai, Wentong Turner, Stephen J. Chen, L. School of Computer Engineering Nanyang Technological University Singapore

This paper describes two adaptive algorithms for dead reckoning in Distributed Interactive Simulation (DIS). The first algorithm is based on the control mechanism of adaptive adjustment of threshold level and the second on automatic selection of extrapolation equation. Since a fixed threshold cannot adequately handle the dynamic relationships between moving entities, a multi-level threshold scheme is proposed. The definition of threshold levels is based on the concepts of area of interest and sensitive region, and the levels of threshold are adaptively adjusted based on the relative distance between entities during the simulation. During the simulation, the motion of an entity may also change from time to time. To optimize the performance, the second adaptive algorithm uses a control mechanism that automatically selects an appropriate extrapolation formula according to the entity's motion. Various experiments were conducted. The results show that the proposed adaptive dead reckoning algorithms can achieve a considerable reduction in the number of update packets while maintaining adequate accuracy in extrapolation. © 2000, UK Simulation Society. All right reserved.

关键词： adaptive algorithms

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Dynamic Transmission Adaptation algorithms for Battery-Free Lorawan Devices

SSRN

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SSRN 2025年

作者： Giuliano, Fabrizio Pagano, Antonino Croce, Daniele Vitale, Gianpaolo Tinnirello, Ilenia CNIT - Consorzio Nazionale Interuniversitario per le Telecomunicazioni Italy University of Palermo Italy ICAR-CNR - Istituto di Calcolo ad Alte Prestazioni Consiglio Nazionale delle Ricerche Palermo Italy University of Catania Italy

Demand for sustainable IoT solutions has increased over the years, with energy-harvesting technologies coming to the fore, and environmental-powered sensors gaining much importance. Indeed, the benefits can be outstanding for batteryless sensors in terms of increased durability, reduced maintenance (no need for battery replacement), and higher resistance to environmental factors. However, such batteryless devices must be accurately designed to cope with time-varying energy sources, such as solar or wind power. In particular, this work investigates adaptive transmission algorithms to optimize the performance and lifetime of LoRa-based batteryless IoT ***, a thorough characterization is carried out concerning the device's power consumption, focusing on both sensor measurement and data transmission operations. The performed analysis takes into account also different network scenarios, considering possible changes of the device parameters. Second, a transmission adaptation scheme for the optimizing data transmission intervals, named Uniform Transmission Adaptation (UTA), is proposed. Finally, tailored energy storage solutions are developed, depending on the available energy capacity and considering direct coupling and the use of renewable sources, like photovoltaic *** large-scale simulations in a massive IoT scenario, we quantitatively assess network performance, energy consumption and network *** findings provide a basis for the design of sensor devices with optimal energy management, in order to meet given reliability requirements, and tackling important challenges of batteryless IoT networks. © 2025, The Authors. All rights reserved.

关键词： adaptive algorithms

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Digital twin of buildings and occupants for emergency evacuation: Framework, technologies, applications and trends

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Advanced Engineering Informatics 2025年 66卷

作者： Lin, Jia-Rui Chen, Ke-Yin Song, Sheng-Yu Cai, Yun-Hong Pan, Peng Deng, Yi-Chuan Department of Civil Engineering Tsinghua University China Key Laboratory of Digital Construction and Digital Twin Ministry of Housing and Urban-Rural Development China School of Civil Engineering and Transportation South China University of Technology China

Buildings face threats from various emergencies, with emergency evacuation being a key measure for occupant safety. However, enhancing evacuation efficiency necessitates detailed studies of building characteristics and human behaviors. Despite this, a systematic review of digital twin technologies for emergency evacuation is still lacking. Therefore, by collecting and analyzing literature from 2004 to 2025 using PRISMA methodology, this study first proposes a conceptual digital twin framework that integrates buildings, occupants, and their interactions, encompassing the entire loop of sensing, updating, simulation, and decision-making. The current research has made significant progresses in areas such as basic virtual modeling, one-way data mapping, and preliminary bidirectional interaction. However, studies and applications of digital twins remain in the developmental stage, with most at maturity levels L0-L2, while L4-L5 applications are still relatively scarce. It is suggested that the future development of digital twin-based evacuation systems must rely on multidisciplinary collaboration to achieve breakthroughs, including optimizing underlying mechanisms to enhance data and system integration;improving sensing accuracy and developing adaptive algorithms for simulation, prediction and assessment;integrating emerging artificial intelligence technologies while addressing data ethics;and enhancing computational efficiency to strengthen system robustness. © 2025 Elsevier Ltd

关键词： adaptive algorithms

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Constant-Factor Distortion Mechanisms for k-Committee Election

arXiv

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arXiv 2025年

作者： Pulyassary, Haripriya Swamy, Chaitanya School of ORIE Cornell University IthacaNY14853 United States Dept. of Combinatorics & Optimization Univ. Waterloo WaterlooONN2L 3G1 Canada

In the k-committee election problem, we wish to aggregate the preferences of n agents over a set of alternatives and select a committee of k alternatives that minimizes the cost incurred by the agents. While we typically assume that agent preferences are captured by a cardinal utility function, in many contexts we only have access to ordinal information, namely the agents’ rankings over the outcomes. As preference rankings are not as expressive as cardinal utilities, a loss of efficiency is inevitable, and is quantified by the notion of distortion. We study the problem of electing a k-committee that minimizes the sum of the -largest costs incurred by the agents, when agents and candidates are embedded in a metric space. This problem is called the -centrum problem and captures both the utilitarian and egalitarian objectives. When k ≥ 2, it is not possible to compute a bounded-distortion committee using purely ordinal information. We develop the first algorithms (that we call mechanisms) for the -centrum problem (when k ≥ 2), which achieve O(1)distortion while eliciting only a very limited amount of cardinal information via value queries. We obtain two types of query-complexity guarantees: O(log k log n) queries per agent, and O(k2 log2 n) queries in total (while achieving O(1)-distortion in both cases). En route, we give a simple adaptive-sampling algorithm for the -centrum k-clustering problem. Copyright © 2025, The Authors. All rights reserved.

关键词： adaptive algorithms

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Underwater Frequency Selection Algorithm Based on the Received Signal

Underwater Frequency Selection Algorithm Based on the Receiv...

引用

International Symposium on Underwater Technology

作者： Raji Alahmad Mohammad Albaroudi Abdullah Alraee Kazuo Ishii Department of Human Intelligence Systems Kyushu Institute of Technology Kitakyushu Fukuoka Japan Department of Life Science and System Engineering Kyushu Institute of Technology Kitakyushu Fukuoka Japan

ISBN: (数字)9798331534189

ISBN: (纸本)9798331534196

Underwater communication is widely regarded as one of the most significant challenges due to the unique physical properties of water. Among the available communication methods, radiofrequency communication offers higher data transmission rates than acoustic communication. However, higher frequencies suffer from substantial attenuation in water, making it difficult to achieve long-distance transmission. Addressing the tradeoff between transmission rate and communication distance is essential for achieving optimal performance. Unlike conventional systems that rely on fixed operating frequencies, this study introduces a dynamic frequency selection algorithm. This algorithm dynamically adjusts the operating frequency in real-time based on channel conditions and transmission rate feedback, ensuring a more adaptive and efficient communication system. To validate this approach, a dipole antenna with multiple impedance matching was designed and tested in a water tank environment. The experimental results revealed that bandwidth performance varied across different frequencies. Transmission rate analysis showed that higher frequencies provided higher data transmission over short distances. Conversely, lower frequencies exhibited better signal stability and reliability for long-distance communication due to their reduced attenuation. These findings highlight the importance of adaptive frequency selection in underwater radiofrequency communication, where a balance between transmission rate and communication distance must be achieved to support various operational requirements.

关键词： Radio frequency Water Underwater communication Dipole antennas Heuristic algorithms adaptive algorithms Bandwidth Attenuation Real-time systems Data communication

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HEX: Hierarchical Emergence Exploitation in Self-Supervised algorithms

HEX: Hierarchical Emergence Exploitation in Self-Supervised ...

引用

IEEE Workshop on Applications of Computer Vision (WACV)

作者： Kiran Kokilepersaud Seulgi Kim Mohit Prabhushankar Ghassan AlRegib OLIVES at the Center for Signal and Information Processing CSIP School of Electrical and Computer Engineering Georgia Institute of Technology Atlanta GA USA

ISBN: (数字)9798331510831

ISBN: (纸本)9798331510848

In this paper, we propose an algorithm that can be used on top of a wide variety of self-supervised (SSL) approaches to take advantage of hierarchical structures that emerge during training. SSL approaches typically work through some invariance term to ensure consistency between similar samples and a regularization term to prevent global dimensional collapse. Dimensional collapse refers to data representations spanning a lower-dimensional subspace. Recent work has demonstrated that the representation space of these algorithms gradually reflects a semantic hierarchical structure as training progresses. Data samples of the same hierarchical grouping tend to exhibit greater dimensional collapse locally compared to the dataset as a whole due to sharing features in common with each other. Ideally, SSL algorithms would take advantage of this hierarchical emergence to have an additional regularization term to account for this local dimensional collapse effect. However, the construction of existing SSL algorithms does not account for this property. To address this, we propose an adaptive algorithm that performs a weighted decomposition of the denominator of the InfoNCE loss into two terms: local hierarchical and global collapse regularization respectively. This decomposition is based on an adaptive threshold that gradually lowers to reflect the emerging hierarchical structure of the representation space throughout training. It is based on an analysis of the cosine similarity distribution of samples in a batch. We demonstrate that this hierarchical emergence exploitation (HEX) approach can be integrated across a wide variety of SSL algorithms. Empirically, we show performance improvements of up to 5.6% relative improvement over baseline SSL approaches on classification accuracy on Imagenet with 100 epochs of training.

关键词： Training Measurement Computer vision Accuracy Semantics Data visualization adaptive algorithms Classification algorithms

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Frankenstein Optimizer: Harnessing the Potential by Revisiting Optimization Tricks

arXiv

引用

arXiv 2025年

作者： Hsu, Chia-Wei Tsou, Nien-Ti Chen, Yu-Cheng Park, Yang Jeong Li, Ju Department of Materials Science and Engineering Massachusetts Institute of Technology CambridgeMA02139 United States Department of Materials Science and Engineering National Yang Ming Chiao Tung University Taiwan Hon Hai Research Institute Taipei Taiwan Department of Nuclear Science and Engineering Massachusetts Institute of Technology CambridgeMA02139 United States

Gradient-based optimization drives the unprecedented performance of modern deep neural network models across diverse applications. adaptive algorithms have accelerated neural network training due to their rapid convergence rates;however, they struggle to find "flat minima" reliably, resulting in suboptimal generalization compared to stochastic gradient descent (SGD). By revisiting various adaptive algorithms’ mechanisms, we propose the Frankenstein optimizer, which combines their advantages. The proposed Frankenstein dynamically adjusts first- and second-momentum coefficients according to the optimizer’s current state to directly maintain consistent learning dynamics and immediately reflect sudden gradient changes. Extensive experiments across several research domains such as computer vision, natural language processing, few-shot learning, and scientific simulations show that Frankenstein surpasses existing adaptive algorithms and SGD empirically regarding convergence speed and generalization performance. Furthermore, this research deepens our understanding of adaptive algorithms through centered kernel alignment analysis and loss landscape visualization during the learning process. © 2025, CC BY.

关键词： adaptive algorithms

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adaptive least square kernel algorithms and applications

Adaptive least square kernel algorithms and applications

引用

International Joint Conference on Neural Networks (IJCNN 02)

作者： Kuh, A Univ Hawaii Dept Elect Engn Honolulu HI 96822 USA

ISBN: (纸本)0780372786

This paper discusses adaptive on-line kernel algorithms and application of these algorithms to signal processing problems. The Support Vector Machine (SVM) is a kernel method technique that has gained widespread acceptance in solving pattern classification and regression problems. SVM solutions generally involve solving a quadratic programming problem making it more difficult for applying these methods to adaptive signal processing problems. In previous work a variant of the SVM has been developed called the least squares SVM (LS-SVM). A solution to the algorithm can be found by solving a set of linear equations which makes on-line adaptive implementation of the algorithm feasible. After discussing some of the differences between the SVM and the LS-SVM we present an adaptive LS-SVM solution and discuss signal processing applications of these algorithms.

关键词： adaptive algorithms

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