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Journal articles on the topic 'Gradient descent ascent'

Author: Grafiati

Published: 7 June 2025

Last updated: 2 August 2025

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1

Lu, Songtao, Kaiqing Zhang, Tianyi Chen, Tamer Başar, and Lior Horesh. "Decentralized Policy Gradient Descent Ascent for Safe Multi-Agent Reinforcement Learning." Proceedings of the AAAI Conference on Artificial Intelligence 35, no. 10 (2021): 8767–75. http://dx.doi.org/10.1609/aaai.v35i10.17062.

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This paper deals with distributed reinforcement learning problems with safety constraints. In particular, we consider that a team of agents cooperate in a shared environment, where each agent has its individual reward function and safety constraints that involve all agents' joint actions. As such, the agents aim to maximize the team-average long-term return, subject to all the safety constraints. More intriguingly, no central controller is assumed to coordinate the agents, and both the rewards and constraints are only known to each agent locally/privately. Instead, the agents are connected by

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Pan, Zibin, Zhichao Wang, Chi Li, et al. "Federated Unlearning with Gradient Descent and Conflict Mitigation." Proceedings of the AAAI Conference on Artificial Intelligence 39, no. 19 (2025): 19804–12. https://doi.org/10.1609/aaai.v39i19.34181.

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Federated Learning (FL) has received much attention in recent years. However, although clients are not required to share their data in FL, the global model itself can implicitly remember clients' local data. Therefore, it’s necessary to effectively remove the target client's data from the FL global model to ease the risk of privacy leakage and implement "the right to be forgotten". Federated Unlearning (FU) has been considered a promising solution to remove data without full retraining. But the model utility easily suffers significant reduction during unlearning due to the gradient conflicts.

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Tang, Zheng, Xu Gang Wang, Hiroki Tamura, and Masahiro Ishii. "An Algorithm of Supervised Learning for Multilayer Neural Networks." Neural Computation 15, no. 5 (2003): 1125–42. http://dx.doi.org/10.1162/089976603765202686.

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A method of supervised learning for multilayer artificial neural networks to escape local minima is proposed. The learning model has two phases: a backpropagation phase and a gradient ascent phase. The backpropagation phase performs steepest descent on a surface in weight space whose height at any point in weight space is equal to an error measure, and it finds a set of weights minimizing this error measure. When the backpropagation gets stuck in local minima, the gradient ascent phase attempts to fill up the valley by modifying gain parameters in a gradient ascent direction of the error measu

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Shen, Zhubin, Jianfeng Li, and Qihui Wu. "A fast adaptive beamformer with sidelobe control based on gradient descent ascent." Signal Processing 206 (May 2023): 108906. http://dx.doi.org/10.1016/j.sigpro.2022.108906.

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Hedworth, Hayden, Jeffrey Page, John Sohl, and Tony Saad. "Investigating Errors Observed during UAV-Based Vertical Measurements Using Computational Fluid Dynamics." Drones 6, no. 9 (2022): 253. http://dx.doi.org/10.3390/drones6090253.

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Unmanned Aerial Vehicles (UAVs) are a popular platform for air quality measurements. For vertical measurements, rotary-wing UAVs are particularly well-suited. However, an important concern with rotary-wing UAVs is how the rotor-downwash affects measurement accuracy. Measurements from a recent field campaign showed notable discrepancies between data from ascent and descent, which suggested the UAV downwash may be the cause. To investigate and explain these observed discrepancies, we use high-fidelity computational fluid dynamics (CFD) simulations to simulate a UAV during vertical flight. We use

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Zhang, Fengjiao, Aoyu Luo, Zongbo Hao, and Juncong Lu. "Two-stream neural network with different gradient update strategies." Journal of Physics: Conference Series 2741, no. 1 (2024): 012018. http://dx.doi.org/10.1088/1742-6596/2741/1/012018.

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Abstract Deep neural networks will be affected by various noises in different scenes. Traditional deep neural networks often use gradient descent algorithms to update parameter weights. When the gradient falls to a certain range, it is easy to fall into the local optimal solution. Although the impulse method and other methods can escape from local optimization in some scenarios, they still have some limitations, which will greatly reduce the application effect of the actual scenes. To solve the above problems, a two-stream neural network with different gradient update strategies was proposed.

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Pendharkar, Parag C. "A comparison of gradient ascent, gradient descent and genetic-algorithm-based artificial neural networks for the binary classification problem." Expert Systems 24, no. 2 (2007): 65–86. http://dx.doi.org/10.1111/j.1468-0394.2007.00421.x.

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Cheng, Jieren, Chen Zhang, Xiangyan Tang, Victor S. Sheng, Zhe Dong, and Junqi Li. "Adaptive DDoS Attack Detection Method Based on Multiple-Kernel Learning." Security and Communication Networks 2018 (October 16, 2018): 1–19. http://dx.doi.org/10.1155/2018/5198685.

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Distributed denial of service (DDoS) attacks has caused huge economic losses to society. They have become one of the main threats to Internet security. Most of the current detection methods based on a single feature and fixed model parameters cannot effectively detect early DDoS attacks in cloud and big data environment. In this paper, an adaptive DDoS attack detection method (ADADM) based on multiple-kernel learning (MKL) is proposed. Based on the burstiness of DDoS attack flow, the distribution of addresses, and the interactivity of communication, we define five features to describe the netw

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Zhang, Ruijia, Mingxi Lei, Meng Ding, Zihang Xiang, Jinhui Xu, and Di Wang. "Improved Rates of Differentially Private Nonconvex-Strongly-Concave Minimax Optimization." Proceedings of the AAAI Conference on Artificial Intelligence 39, no. 21 (2025): 22524–32. https://doi.org/10.1609/aaai.v39i21.34410.

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In this paper, we study the problem of (finite sum) minimax optimization in the Differential Privacy (DP) model. Unlike most of the previous studies on the (strongly) convex-concave settings or loss functions satisfying the Polyak-Lojasiewicz condition, here we mainly focus on the nonconvex-strongly-concave one, which encapsulates many models in deep learning such as deep AUC maximization. Specifically, we first analyze a DP version of Stochastic Gradient Descent Ascent (SGDA) and show the utility bound in terms of the Euclidean norm of the gradient for the empirical risk function. We then pro

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Bieliński, Adrian, Izabela Rojek, and Dariusz Mikołajewski. "Comparison of Selected Machine Learning Algorithms in the Analysis of Mental Health Indicators." Electronics 12, no. 21 (2023): 4407. http://dx.doi.org/10.3390/electronics12214407.

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Machine learning is increasingly being used to solve clinical problems in diagnosis, therapy and care. Aim: the main aim of the study was to investigate how the selected machine learning algorithms deal with the problem of determining a virtual mental health index. Material and Methods: a number of machine learning models based on Stochastic Dual Coordinate Ascent, limited-memory Broyden–Fletcher–Goldfarb–Shanno, Online Gradient Descent, etc., were built based on a clinical dataset and compared based on criteria in the form of learning time, running time during use and regression accuracy. Res

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Dong, Mingrong, Yixuan Yang, Kai Zeng, Qingwang Wang, and Tao Shen. "Implicit Sharpness-Aware Minimization for Domain Generalization." Remote Sensing 16, no. 16 (2024): 2877. http://dx.doi.org/10.3390/rs16162877.

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Domain generalization (DG) aims to learn knowledge from multiple related domains to achieve a robust generalization performance in unseen target domains, which is an effective approach to mitigate domain shift in remote sensing image classification. Although the sharpness-aware minimization (SAM) method enhances DG capability and improves remote sensing image classification performance by promoting the convergence of the loss minimum to a flatter loss surface, the perturbation loss (maximum loss within the neighborhood of a local minimum) of SAM fails to accurately measure the true sharpness o

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12

Kamaraj, Michael, and Balakrishnan. "Global Energy Minimization and Optimization of Multi-Target Tracking." Journal of Computational and Theoretical Nanoscience 14, no. 1 (2017): 704–14. http://dx.doi.org/10.1166/jctn.2017.6261.

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The recent multiple target tracking methods aim to obtain the best possible number of trajectories within the time frame, and few constraints have been set to handle the wide area of trajectories by discrete mapping. In this novel approach of multi target tracking, energy terms are formulated to attain the global optimization which includes the entire representation of the issues such as target tracking, operational representation, collision handling and trajectory processing. Furthermore, two optimization strategies such as the gradient descent which is performed on multiple feature space to

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Al-Khazraji, Lafta R., Ayad R. Abbas, and Abeer S. Jamil. "Employing Neural Style Transfer for Generating Deep Dream Images." ARO-THE SCIENTIFIC JOURNAL OF KOYA UNIVERSITY 10, no. 2 (2022): 134–41. http://dx.doi.org/10.14500/aro.11051.

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In recent years, deep dream and neural style transfer emerged as hot topics in deep learning. Hence, mixing those two techniques support the art and enhance the images that simulate hallucinations among psychiatric patients and drug addicts. In this study, our model combines deep dream and neural style transfer (NST) to produce a new image that combines the two technologies. VGG-19 and Inception v3 pre-trained networks are used for NST and deep dream, respectively. Gram matrix is a vital process for style transfer. The loss is minimized in style transfer while maximized in a deep dream using g

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Raizada, S., and H. S. S. Sinha. "Some new features of electron density irregularities over SHAR during strong spread F." Annales Geophysicae 18, no. 2 (2000): 141–51. http://dx.doi.org/10.1007/s00585-000-0141-8.

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Abstract. An RH-560 rocket flight was conducted from Sriharikota rocket range (SHAR) (14°N, 80°E, dip latitude 5.5°N) to study electron density and electric field irregularities during spread F. The rocket was launched at 2130 local time (LT) and it attained an apogee of 348 km. Results of electron density fluctuations are presented here. Two extremely sharp layers of very high electron density were observed at 105 and 130 km. The electron density increase in these layers was by a factor of 50 in a vertical extent of 10 km. Large depletions in electron density were observed around 175 and 238

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Feng, Juan, and Jianping Li. "Contrasting Impacts of Two Types of ENSO on the Boreal Spring Hadley Circulation." Journal of Climate 26, no. 13 (2013): 4773–89. http://dx.doi.org/10.1175/jcli-d-12-00298.1.

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Abstract The possible influences of two types of ENSO [i.e., the canonical ENSO and ENSO Modoki (EM)] on Hadley circulation (HC) during the boreal spring are investigated during 1979–2010. El Niño events are featured with a symmetric pattern in equatorial zonal-mean sea surface temperature anomalies (SSTA), with a maximum around the equator. In contrast, the zonal-mean SSTA associated with El Niño Modoki events shows an asymmetric structure with a maximum around 10°N. The contrasting underlying thermal structures corresponding with ENSO and EM have opposite impacts on the simultaneous HC. In E

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Ying, Donghao, Mengzi Amy Guo, Yuhao Ding, Javad Lavaei, and Zuo-Jun Shen. "Policy-Based Primal-Dual Methods for Convex Constrained Markov Decision Processes." Proceedings of the AAAI Conference on Artificial Intelligence 37, no. 9 (2023): 10963–71. http://dx.doi.org/10.1609/aaai.v37i9.26299.

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We study convex Constrained Markov Decision Processes (CMDPs) in which the objective is concave and the constraints are convex in the state-action occupancy measure. We propose a policy-based primal-dual algorithm that updates the primal variable via policy gradient ascent and updates the dual variable via projected sub-gradient descent. Despite the loss of additivity structure and the nonconvex nature, we establish the global convergence of the proposed algorithm by leveraging a hidden convexity in the problem, and prove the O(T^-1/3) convergence rate in terms of both optimality gap and const

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Rozada, Sergio, Dongsheng Ding, Antonio G. Marques, and Alejandro Ribeiro. "Deterministic Policy Gradient Primal-Dual Methods for Continuous-Space Constrained MDPs." Proceedings of the AAAI Conference on Artificial Intelligence 39, no. 19 (2025): 20200–20208. https://doi.org/10.1609/aaai.v39i19.34225.

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We study the problem of computing deterministic optimal policies for constrained Markov decision processes (MDPs) with continuous state and action spaces, which are widely encountered in constrained dynamical systems. Designing deterministic policy gradient methods in continuous state and action spaces is particularly challenging due to the lack of enumerable state-action pairs and the adoption of deterministic policies, hindering the application of existing policy gradient methods for constrained MDPs. To this end, we develop a deterministic policy gradient primal-dual method to find an optim

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18

Westrick, Kristen Y., Bradley Serack, William H. Dantzler, and Thomas L. Pannabecker. "Axial compartmentation of descending and ascending thin limbs of Henle's loops." American Journal of Physiology-Renal Physiology 304, no. 3 (2013): F308—F316. http://dx.doi.org/10.1152/ajprenal.00547.2012.

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In the inner medulla, radial organization of nephrons and blood vessels around collecting duct (CD) clusters leads to two lateral interstitial regions and preferential intersegmental fluid and solute flows. As the descending (DTLs) and ascending thin limbs (ATLs) pass through these regions, their transepithelial fluid and solute flows are influenced by variable transepithelial solute gradients and structure-to-structure interactions. The goal of this study was to quantify structure-to-structure interactions, so as to better understand compartmentation and flows of transepithelial water, NaCl,

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19

Önal, Emre, and Abdullah Bülbül. "Computational Game Unit Balancing based on Game Theory." JUCS - Journal of Universal Computer Science 31, no. (1) (2025): 3–21. https://doi.org/10.3897/jucs.121185.

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Optimizing game elements through iterative human playtests can be time-consuming and insufficient for games with complex intransitive mechanics. Imbalances in games often require the release of numerous balance patches. We present a computational method for making each game unit equally preferable against a uniform play strategy. We leverage concepts from game theory to model intricate relationships among intransitive entities. Matching units against each other is modeled as a symmetric zero-sum game, where unit selection represents a strategy and the error is quantified using payoff values de

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20

Tsuchiya, Takao, and Masashi Kanamori. "Two-dimensional finite difference-time domain analysis of focus boom noise with velocity disturbance in the atmosphere." INTER-NOISE and NOISE-CON Congress and Conference Proceedings 263, no. 6 (2021): 589–97. http://dx.doi.org/10.3397/in-2021-1576.

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In this paper, two-dimensional linear sound wave analysis in the stratified atmosphere with temperature gradient and velocity disturbance is numerically applied to the analysis and prediction of focus boom noise. Focus boom occurs when a supersonic transport accelerates or ascent or descent maneuvers at supersonic speed. Its overpressure is typically more than three times greater than that of a cruise sonic boom. As a result, supersonic transports in future commercial operation are likely to face restrictions on their flight conditions. The compact-explicit finite difference-time domain method

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21

Norris, Joel R., and Sam F. Iacobellis. "North Pacific Cloud Feedbacks Inferred from Synoptic-Scale Dynamic and Thermodynamic Relationships." Journal of Climate 18, no. 22 (2005): 4862–78. http://dx.doi.org/10.1175/jcli3558.1.

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Abstract Daily satellite cloud observations and reanalysis dynamical parameters are analyzed to determine how midtropospheric vertical velocity and advection over the sea surface temperature gradient control midlatitude North Pacific cloud properties. Optically thick clouds with high tops are generated by synoptic ascent, but two different cloud regimes occur under synoptic descent. When vertical motion is downward during summer, extensive stratocumulus cloudiness is associated with near-surface northerly wind, while frequent cloudless pixels occur with southerly wind. Examination of ship-repo

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Ni, Shiwen, Jiawen Li, and Hung-Yu Kao. "HAT4RD: Hierarchical Adversarial Training for Rumor Detection in Social Media." Sensors 22, no. 17 (2022): 6652. http://dx.doi.org/10.3390/s22176652.

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With the development of social media, social communication has changed. While this facilitates people’s communication and access to information, it also provides an ideal platform for spreading rumors. In normal or critical situations, rumors can affect people’s judgment and even endanger social security. However, natural language is high-dimensional and sparse, and the same rumor may be expressed in hundreds of ways on social media. As such, the robustness and generalization of the current rumor detection model are in question. We proposed a novel hierarchical adversarial training method for

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23

Hu, Feng, and Tim Li. "Effects of MJO Vertically Tilted Structure on Its Phase Speed from the Moisture Mode Theory Perspective." Journal of Climate 34, no. 11 (2021): 4505–20. http://dx.doi.org/10.1175/jcli-d-20-0732.1.

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AbstractThe effect of vertically tilted structure (VTS) of the MJO on its phase propagation speed was investigated through the diagnosis of ERA-Interim reanalysis data during 1979–2012. A total of 84 eastward propagating MJO events were selected. It was found that all MJO events averaged throughout their life cycles exhibited a clear VTS, and the tilting strength was significantly positively correlated to the phase speed. The physical mechanism through which the VTS influenced the phase speed was investigated. On the one hand, a stronger VTS led to a stronger vertical overturning circulation a

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Ding, Guanwen, Xizhe Zang, Xuehe Zhang, Changle Li, Yanhe Zhu, and Jie Zhao. "Robot Task-Constrained Optimization and Adaptation with Probabilistic Movement Primitives." Biomimetics 9, no. 12 (2024): 738. https://doi.org/10.3390/biomimetics9120738.

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Enabling a robot to learn skills from a human and adapt to different task scenarios will enable the use of robots in manufacturing to improve efficiency. Movement Primitives (MPs) are prominent tools for encoding skills. This paper investigates how to learn MPs from a small number of human demonstrations and adapt to different task constraints, including waypoints, joint limits, virtual walls, and obstacles. Probabilistic Movement Primitives (ProMPs) model movements with distributions, thus providing the robot with additional freedom for task execution. We provide the robot with three modes to

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Lehre, Per Kristian, and Shishen Lin. "Towards Runtime Analysis of Population-Based Co-evolutionary Algorithms on Sparse Binary Zero-Sum Game." Proceedings of the AAAI Conference on Artificial Intelligence 39, no. 25 (2025): 27054–62. https://doi.org/10.1609/aaai.v39i25.34912.

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The maximin optimisation problem, inspired by Von Neumann’s work (von Neumann 1928) and widely applied in adversarial optimisation, has become a key research area in machine learning. Gradient Descent Ascent (GDA) is a common method for solving these problems but requires the pay-off function to be differentiable, making it unsuitable for discrete or binary functions that often occur in game-theoretical scenarios. Co-evolutionary algorithms (CoEAs), which are derivative-free, offer an alternative to these problems. However, the theoretical understanding of CoEAs is still limited. This paper pr

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Ma, Jing, Yaping Yuan, Li Zhang, et al. "Evaluation of Right Ventricular Function and Myocardial Microstructure in Fetal Hypoplastic Left Heart Syndrome." Journal of Clinical Medicine 11, no. 15 (2022): 4456. http://dx.doi.org/10.3390/jcm11154456.

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Right ventricular (RV) function is one of the critical factors affecting the prognosis of fetuses with hypoplastic left heart syndrome (HLHS). Our study objectives included assessment of cardiac function and comprehensive measurement of cardiac microstructure. We retrospectively studied 42 fetuses diagnosed as HLHS by echocardiography. Myocardial deformation of the right ventricular wall was calculated automatically in offline software. Postmortem cardiac imaging for three control fetal hearts and four HLHS specimens was performed by a 9.4T DTI scanner. Myocardial deformation parameters of the

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Saint-Lu, Marion, Robin Chadwick, F. Hugo Lambert, et al. "Influences of Local and Remote Conditions on Tropical Precipitation and Its Response to Climate Change." Journal of Climate 33, no. 10 (2020): 4045–63. http://dx.doi.org/10.1175/jcli-d-19-0450.1.

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AbstractBy comparing a single-column model (SCM) with closely related general circulation models (GCMs), precipitation changes that can be diagnosed from local changes in surface temperature (TS) and relative humidity (RHS) are separated from more complex responses. In the SCM setup, the large-scale tropical circulation is parameterized to respond to the surface temperature departure from a prescribed environment, following the weak temperature gradient (WTG) approximation and using the damped gravity wave (DGW) parameterization. The SCM is also forced with moisture variations. First, it is fo

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Yan, Yan. "Enhance Robustness of Machine Learning with Improved Efficiency." Proceedings of the AAAI Conference on Artificial Intelligence 37, no. 13 (2023): 15461. http://dx.doi.org/10.1609/aaai.v37i13.26828.

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Robustness of machine learning, often referring to securing performance on different data, is always an active field due to the ubiquitous variety and diversity of data in practice. Many studies have been investigated to enhance the learning process robust in recent years. To this end, there is usually a trade-off that results in somewhat extra cost, e.g., more data samples, more complicated objective functions, more iterations to converge in optimization, etc. Then this problem boils down to finding a better trade-off under some conditions. My recent research focuses on robust machine learnin

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Ding, Guanwen, Xizhe Zang, Xuehe Zhang, Changle Li, Yanhe Zhu, and Jie Zhao. "A Human–Robot Skill Transfer Strategy with Task-Constrained Optimization and Real-Time Whole-Body Adaptation." Applied Sciences 15, no. 6 (2025): 3171. https://doi.org/10.3390/app15063171.

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Human–robot skill transfer enables robots to learn skills from humans and adapt to new task-constrained scenarios. During task execution, robots are expected to react in real-time to unforeseen dynamic obstacles. This paper proposes an integrated human–robot skill transfer strategy with offline task-constrained optimization and real-time whole-body adaptation. Specifically, we develop the via-point trajectory generalization method to learn from only one human demonstration. To incrementally incorporate multiple human skill variations, we encode initial distributions for each skill with Joint P

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Liu, Xiaoning, Zhihao Ke, Yining Chen, and Zigang Deng. "The feasibility of designing a back propagation neural network to predict the levitation force of high-temperature superconducting magnetic levitation." Superconductor Science and Technology 35, no. 4 (2022): 044004. http://dx.doi.org/10.1088/1361-6668/ac55f5.

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Abstract The levitation force between the superconductor and the magnet is highly nonlinear and affected by the coupling of multiple factors, which brings many obstacles to research and application. In addition to experimental methods and finite element simulations, the booming artificial neural network (ANN) which is adept at continuous nonlinear fitting may provide another solution to predict the levitation force. And this topic has not been deeply investigated so far. Therefore, this study aims to apply the ANN to predict the levitation force, and a typical neural network applied with the b

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Chen, Sue, Russell L. Elsberry, and Patrick A. Harr. "Modeling Interaction of a Tropical Cyclone with Its Cold Wake." Journal of the Atmospheric Sciences 74, no. 12 (2017): 3981–4001. http://dx.doi.org/10.1175/jas-d-16-0246.1.

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Abstract This study first examines the tropical cyclone (TC) intensity response to its cold wake with time-invariant, stationary cold wakes and an uncoupled version of COAMPS-TC, and second with simulated cold wakes from the fully coupled version. The objective of the uncoupled simulations with the time-invariant cold wake is to fix the thermodynamic response and to isolate the dynamic response of the TC to the cold wake. While the stationary TC over a cold wake has an immediate intensity decrease, the intensity decrease with a long trailing wake from the moving TC was delayed. This time delay

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JANKOVIC, MARKO, and HIDEMITSU OGAWA. "TIME-ORIENTED HIERARCHICAL METHOD FOR COMPUTATION OF PRINCIPAL COMPONENTS USING SUBSPACE LEARNING ALGORITHM." International Journal of Neural Systems 14, no. 05 (2004): 313–23. http://dx.doi.org/10.1142/s0129065704002091.

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Principal Component Analysis (PCA) and Principal Subspace Analysis (PSA) are classic techniques in statistical data analysis, feature extraction and data compression. Given a set of multivariate measurements, PCA and PSA provide a smaller set of "basis vectors" with less redundancy, and a subspace spanned by them, respectively. Artificial neurons and neural networks have been shown to perform PSA and PCA when gradient ascent (descent) learning rules are used, which is related to the constrained maximization (minimization) of statistical objective functions. Due to their low complexity, such al

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Stechmann, Samuel N., and Bjorn Stevens. "Multiscale Models for Cumulus Cloud Dynamics." Journal of the Atmospheric Sciences 67, no. 10 (2010): 3269–85. http://dx.doi.org/10.1175/2010jas3380.1.

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Abstract Cumulus clouds involve processes on a vast range of scales—including cloud droplets, turbulent mixing, and updrafts and downdrafts—and it is often difficult to determine how processes on different scales interact with each other. In this article, several multiscale asymptotic models are derived for cumulus cloud dynamics in order to (i) provide a systematic scale analysis on each scale and (ii) clarify the nature of interactions between different scales. In terms of scale analysis, it is shown that shallow cumulus updrafts can be described by balanced dynamics with a balance between s

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Al-Mutairi, Motirh, Abdulhaleem Labban, Abdallah Abdeldym, Ahmed Alkhouly, Heshmat Abdel Basset, and Mostafa Morsy. "Diagnostic Study of a Severe Dust Storm over North Africa and the Arabian Peninsula." Atmosphere 14, no. 2 (2023): 196. http://dx.doi.org/10.3390/atmos14020196.

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This work aimed to study the synoptic evolution and dynamics of the dust activity associated with the desert cyclone occurring over North Africa and the Arabian Peninsula on 4–8 April 2007 based on ECMWF analysis (ERA5) data. This desert cyclone formed over North Africa (Algeria) in the lee of the Atlas Mountains in response to a powerful upper-level trough transporting cold air into northern Africa coming from high latitudes. The development of the cyclone was initiated when the contrast in temperature between the Mediterranean Sea and northern Africa (the desert) was strong, which increased

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Belkhouja, Taha, Yan Yan, and Janardhan Rao Doppa. "Training Robust Deep Models for Time-Series Domain: Novel Algorithms and Theoretical Analysis." Proceedings of the AAAI Conference on Artificial Intelligence 36, no. 6 (2022): 6055–63. http://dx.doi.org/10.1609/aaai.v36i6.20552.

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Despite the success of deep neural networks (DNNs) for real-world applications over time-series data such as mobile health, little is known about how to train robust DNNs for time-series domain due to its unique characteristics compared to images and text data. In this paper, we fill this gap by proposing a novel algorithmic framework referred as RObust Training for Time-Series (RO-TS) to create robust deep models for time-series classification tasks. Specifically, we formulate a min-max optimization problem over the model parameters by explicitly reasoning about the robustness criteria in ter

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Chen, Baohua, and Chuntao Liu. "Warm Organized Rain Systems over the Tropical Eastern Pacific." Journal of Climate 29, no. 9 (2016): 3403–22. http://dx.doi.org/10.1175/jcli-d-15-0177.1.

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Abstract This study uses 16-yr Tropical Rainfall Measuring Mission (TRMM) radar precipitation feature (RPF) data to characterize warm rain systems in the tropics with large horizontal extensions, referred to as warm organized rain systems. The systems are selected by specifying the RPFs with minimum infrared brightness temperature warmer than 0°C and rain area greater than 500 km2. ERA-Interim atmospheric fields and SST from NOAA are analyzed to highlight the environmental characteristics of warm organized rain systems. Warm organized systems occur over specific oceanic regions, including the

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Weigelt, A., R. Ebinghaus, N. Pirrone, et al. "Tropospheric mercury vertical profiles between 500 and 10 000 m in central Europe." Atmospheric Chemistry and Physics Discussions 15, no. 20 (2015): 28217–47. http://dx.doi.org/10.5194/acpd-15-28217-2015.

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Abstract. Measurements of the vertical distribution of atmospheric mercury (Hg) are rare, because airborne measurements are expensive and labour intensive. Consequently, only a few vertical Hg profile measurements have been reported since the 1970s. Besides the CARIBIC passenger aircraft observations, the latest vertical profile over Europe was measured in 1996. Within the Global Mercury Observation System (GMOS) project four vertical profiles were taken on board research aircraft (CASA-212) in August 2013 in background air over different locations in Slovenia and Germany. Each vertical profil

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Weigelt, Andreas, Ralf Ebinghaus, Nicola Pirrone, et al. "Tropospheric mercury vertical profiles between 500 and 10 000 m in central Europe." Atmospheric Chemistry and Physics 16, no. 6 (2016): 4135–46. http://dx.doi.org/10.5194/acp-16-4135-2016.

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Abstract. The knowledge of the vertical distribution of atmospheric mercury (Hg) plays an important role in determining the transport and cycling of mercury. However, measurements of the vertical distribution are rare, because airborne measurements are expensive and labour intensive. Consequently, only a few vertical Hg profile measurements have been reported since the 1970s. Besides the Civil Aircraft for the Regular Investigation of the atmosphere Based on an Instrument Container (CARIBIC) observations, the latest vertical profile over Europe was measured in 1996. Within the Global Mercury O

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Chen, Mengyun, Kaixin Gao, Xiaolei Liu, et al. "THOR, Trace-based Hardware-driven Layer-Oriented Natural Gradient Descent Computation." Proceedings of the AAAI Conference on Artificial Intelligence 35, no. 8 (2021): 7046–54. http://dx.doi.org/10.1609/aaai.v35i8.16867.

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It is well-known that second-order optimizer can accelerate the training of deep neural networks, however, the huge computation cost of second-order optimization makes it impractical to apply in real practice. In order to reduce the cost, many methods have been proposed to approximate a second-order matrix. Inspired by KFAC, we propose a novel Trace-based Hardware-driven layer-ORiented Natural Gradient Descent Computation method, called THOR, to make the second-order optimization applicable in the real application models. Specifically, we gradually increase the update interval and use the matr

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Nicholls, Melville E., Roger A. Pielke Sr., Donavan Wheeler, Gustavo Carrio, and Warren P. Smith. "A numerical modelling investigation of the role of diabatic heating and cooling in the development of a mid-level vortex prior to tropical cyclogenesis – Part 1: The response to stratiform components of diabatic forcing." Atmospheric Chemistry and Physics 18, no. 19 (2018): 14393–416. http://dx.doi.org/10.5194/acp-18-14393-2018.

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Abstract. Mid-tropospheric mesoscale convective vortices have been often observed to precede tropical cyclogenesis. Moreover, recent cloud-resolving numerical modelling studies that are initialized with a weak cyclonic mid-tropospheric vortex sometimes show a considerable intensification of the mid-level circulation prior to the development of the strong cyclonic surface winds that characterize tropical cyclogenesis. The objective of this two-part study is to determine the processes that lead to the development of a prominent mid-level vortex during a simulation of the transformation of a trop

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GILKS, S. J., and J. P. HAGUE. "MOUNTAIN TRAIL FORMATION AND THE ACTIVE WALKER MODEL." International Journal of Modern Physics C 20, no. 06 (2009): 869–90. http://dx.doi.org/10.1142/s0129183109014059.

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We extend the active walker model to address the formation of paths on gradients, which have been observed to have a zigzag form. Our extension includes a new rule, which prohibits direct descent or ascent on steep inclines, simulating aversion to falling. Further augmentation of the model stops walkers from changing direction very rapidly as that would likely lead to a fall. The extended model predicts paths with qualitatively similar forms to the observed trails, but only if the terms suppressing sudden direction changes are included. The need to include terms into the model that stop rapid

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Hung, C. Y., P. Aussillous, and H. Capart. "Granular surface avalanching induced by drainage from a narrow silo." Journal of Fluid Mechanics 856 (October 4, 2018): 444–69. http://dx.doi.org/10.1017/jfm.2018.650.

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Using theory and experiments, we investigate granular surface avalanching due to material outflow from a narrow silo. The assumed silo geometry is a deep rectangular box, of moderate spanwise width and small gap thickness between smooth front and back walls. A small orifice deep below the free surface lets grains drain out at a constant rate. The resulting granular flows can therefore be assumed quasi-two-dimensional and quasi-steady over most of the surface descent history. To model these flows, we couple a kinematic model of deep granular flow with a dynamic model of shallow surface avalanch

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Haghighi, Anisa N., Ryan D. Nolin, Gary D. Pundsack, Nick Craine, Aliaksei Stratsilatau, and Sean C. C. Bailey. "High-altitude balloon-launched uncrewed aircraft system measurements of atmospheric turbulence and qualitative comparison with infrasound microphone response." Atmospheric Measurement Techniques 17, no. 16 (2024): 4863–89. http://dx.doi.org/10.5194/amt-17-4863-2024.

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Abstract. This study investigates the use of a balloon-launched uncrewed aircraft system (UAS) for the measurement of turbulence in the troposphere and lower stratosphere. The UAS was a glider which could conduct an automated descent following a designated flight trajectory and was equipped with in situ sensors for measuring thermodynamic and kinematic atmospheric properties. In addition, this aircraft was equipped with an infrasonic microphone to assess its suitability for the remote detection of clear-air turbulence. The capabilities of the UAS and sensing systems were tested during three fl

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Delfin, Leandro Morera, Raul Pinto Elias, Humberto de Jesus Ochoa Dominguez, and Osslan Osiris Vergara Villegas. "Driving Maximal Frequency Content and Natural Slopes Sharpening for Image Amplification with High Scale Factor." Current Medical Imaging Formerly Current Medical Imaging Reviews 16, no. 1 (2020): 36–49. http://dx.doi.org/10.2174/1573405614666180319160045.

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Background: In this paper, a method for adaptive Pure Interpolation (PI) in the frequency domain, with gradient auto-regularization, is proposed. Methods: The input image is transformed into the frequency domain and convolved with the Fourier Transform (FT) of a 2D sampling array (interpolation kernel) of initial size L × M. The Inverse Fourier Transform (IFT) is applied to the output coefficients and the edges are detected and counted. To get a denser kernel, the sampling array is interpolated in the frequency domain and convolved again with the transform coefficients of the original image of

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Sekula, Piotr, Miroslaw Zimnoch, Jakub Bartyzel, Anita Bokwa, Michal Kud, and Jaroslaw Necki. "Ultra-Light Airborne Measurement System for Investigation of Urban Boundary Layer Dynamics." Sensors 21, no. 9 (2021): 2920. http://dx.doi.org/10.3390/s21092920.

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Winter smog episodes are a severe problem in many cities around the world. The following two mechanisms are responsible for influencing the level of pollutant concentrations: emission of pollutants from different sources and associated processes leading to formation of secondary aerosols in the atmosphere and meteorology, including advection, which is stimulated by horizontal wind, and convection, which depends on vertical air mass movements associated with boundary layer stability that are determined by vertical temperature and humidity gradients. The aim of the present study was to evaluate

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Trier, Stanley B., and Christopher A. Davis. "Mesoscale Convective Vortices Observed during BAMEX. Part II: Influences on Secondary Deep Convection." Monthly Weather Review 135, no. 6 (2007): 2051–75. http://dx.doi.org/10.1175/mwr3399.1.

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Abstract Observations from the Bow Echo and Mesoscale Convective Vortex (MCV) Experiment are used to examine the role of the five mesoscale convective vortices described in Part I on heavy precipitation during the daytime heating cycle. Persistent widespread stratiform rain without deep convection occurs for two strong MCVs in conditionally stable environments with strong vertical shear. Two other MCVs in moderate-to-strong vertical shear have localized redevelopment of deep convection (termed secondary convection) on their downshear side, where conditional instability exists. The strongest of

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Paris, J. D., A. Stohl, P. Ciais, et al. "Source-receptor relationships for airborne measurements of CO<sub>2</sub>, CO and O<sub>3</sub> above Siberia: a cluster-based approach." Atmospheric Chemistry and Physics Discussions 9, no. 2 (2009): 6207–45. http://dx.doi.org/10.5194/acpd-9-6207-2009.

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Abstract. We analysed three intensive campaigns above Siberia resulting in a total of ~70 h of continuous CO2, CO and O3 measurements. The flight route consists of consecutive ascents and descents between Novosibirsk (55° N, 82° E) and Yakutsk (62° N, 129° E). Our data analysis uses clustering of footprints obtained with the Lagrangian particle dispersion model FLEXPART. The model-based technique was found to be able to separate efficiently tracers' concentrations. High CO and O3 concentrations (median values 121 ppb and 54.5 pb respectively) were found in clusters associated with fires in Kaz

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Schultz, David M. "A Review of Cold Fronts with Prefrontal Troughs and Wind Shifts." Monthly Weather Review 133, no. 8 (2005): 2449–72. http://dx.doi.org/10.1175/mwr2987.1.

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Abstract The conceptual model of a classical surface-based cold front consists of a sharp temperature decrease coincident with a pressure trough and a distinct wind shift at the surface. Many cold fronts, however, do not conform to this model—time series at a single surface station may possess a pressure trough and wind shift in the warm air preceding the cold front (hereafter called a prefrontal trough and prefrontal wind shift, respectively). Although many authors have recognized these prefrontal features previously, a review of the responsible mechanisms has not been performed to date. This

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De Monte, Silvia, Cedric Cotté, Francesco d'Ovidio, Marina Lévy, Matthieu Le Corre, and Henri Weimerskirch. "Frigatebird behaviour at the ocean–atmosphere interface: integrating animal behaviour with multi-satellite data." Journal of The Royal Society Interface 9, no. 77 (2012): 3351–58. http://dx.doi.org/10.1098/rsif.2012.0509.

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Marine top predators such as seabirds are useful indicators of the integrated response of the marine ecosystem to environmental variability at different scales. Large-scale physical gradients constrain seabird habitat. Birds however respond behaviourally to physical heterogeneity at much smaller scales. Here, we use, for the first time, three-dimensional GPS tracking of a seabird, the great frigatebird ( Fregata minor ), in the Mozambique Channel. These data, which provide at the same time high-resolution vertical and horizontal positions, allow us to relate the behaviour of frigatebirds to th

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Spinner, Robert J., Kimberly K. Amrami, Alexandra P. Wolanskyj, et al. "Dynamic phases of peroneal and tibial intraneural ganglia formation: a new dimension added to the unifying articular theory." Neurosurgical Focus 22, no. 6 (2007): 1–12. http://dx.doi.org/10.3171/foc.2007.22.6.1.

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Object The pathogenesis of intraneural ganglia has been a controversial issue for longer than a century. Recently the authors identified a stereotypical pattern of occurrence of peroneal and tibial intraneural ganglia, and based on an understanding of their pathogenesis provided a unifying articular explanation. Atypical features, which occasionally are observed, have offered an opportunity to verify further and expand on the authors' proposed theory. Methods Three unusual cases are presented to exemplify the dynamic features of peroneal and tibial intraneural ganglia formation. Results Two pa

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