3D Ultrasound Imaging of Residual Limbs With Camera-Based Motion Compensation by Ranger, Bryan J., Feigin, Micha, Zhang, Xiang, Moerman, Kevin M., Herr, Hugh M., Anthony, Brian W.

“…Our system employs a mechanized water tank setup to scan a limb with a clinical ultrasound transducer and 3D optical imagery to track motion during a scan. The iterative closest point algorithm is utilized to compensate for motion and stitch the images into a final dataset. …”
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Learning stabilizable nonlinear dynamics with contraction-based regularization by Singh, Sumeet, Richards, Spencer M, Sindhwani, Vikas, Slotine, Jean-Jacques E, Pavone, Marco

“…Finally, we utilize random matrix feature approximations to reduce the dimensionality of the search parameters and formulate an iterative convex optimization algorithm that jointly fits the dynamics functions and searches for a certificate of stabilizability. …”
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Morphological Types of DM Halos in Milky Way-like Galaxies in the TNG50 Simulation: Simple, Twisted, or Stretched by Emami, Razieh, Genel, Shy, Hernquist, Lars, Alcock, Charles, Bose, Sownak, Weinberger, Rainer, Vogelsberger, Mark, Marinacci, Federico, Loeb, Abraham, Torrey, Paul, Forbes, John C

“…Using an enclosed volume iterative method, we infer an oblate-to-triaxial shape for the DM halo with median <jats:italic>T</jats:italic> ≃ 0.24. …”
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Toward Information-Driven and Risk-Bounded Autonomy for Adaptive Science and Exploration by Ayton, Benjamin J, Reeves, Marlyse, Timmons, Eric, Williams, Brian C, Ingham, Michel D

“…This task division leads to multiple design iterations between the science and engineering operations which results in compromised, conservative operations that reduce science return and are more brittle than desired. …”
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Consensus Statement on Ethical & Safety Practices for Conducting Digital Monitoring Studies with People at Risk of Suicide and Related Behaviors by Nock, Matthew K, Kleiman, Evan M, Abraham, Melissa, Bentley, Kate H, Brent, David A, Buonopane, Ralph J, Castro‐Ramirez, Franckie, Cha, Christine B, Dempsey, Walter, Draper, John, Glenn, Catherine R, Harkavy‐Friedman, Jill, Hollander, Michael R, Huffman, Jeffrey C, Lee, Hye In S, Millner, Alexander J, Mou, David, Onnela, Jukka‐Pekka, Picard, Rosalind W., Quay, Heather M, Rankin, Osiris, Sewards, Shannon, Torous, John, Wheelis, Joan, Whiteside, Ursula, Siegel, Galia, Ordóñez, Anna E, Pearson, Jane L

“…Twenty-four experts including scientists, clinicians, ethicists, legal experts, and those with lived experience provided input into an iterative, multi-stage survey, and discussion process. …”
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Who2chat: A Social Networking System for Academic Researchers in Virtual Social Hours Enabling Coordinating, Overcoming Barriers and Social Signaling by Park, Soya, Song, Jaeyoon, Karger, David R., Malone, Thomas W.

“…Who2chat allows academic researchers to create a research profile and express their research interests, find researchers with similar interests, overcome social barriers, and coordinate and start video chats, all within a single interface. We engaged in an iterative design process by deploying Who2chat at academic conferences. …”
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The proper treatment of language acquisition and change in a population setting by Niyogi, Partha, Berwick, Robert C.

“…This paper contrasts 2 such models. In the first, iterated learning (IL), each learner receives PLD from one target grammar but different learners can have different targets. …”
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Regression-based LP Solver for Chance-Constrained Finite Horizon Optimal Control with Nonconvex Constraints by Banerjee, Ashis, Ono, Masahiro, Roy, Nicholas, Williams, Brian Charles

“…Our previous work [1] proposed a branch and bound-based algorithm that can find a near-optimal solution by iteratively solving non-linear convex optimization problems, as well as their LP relaxations called Fixed Risk Relaxation (FRR) problems. …”
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Protecting Circuits from Computationally Bounded and Noisy Leakage by Faust, Sebastian, Rabin, Tal, Reyzin, Leonid, Tromer, Eran, Vaikuntanathan, Vinod

“…However, we assume that the apparatus is limited in the amount of output bits per iteration and the ability to decode certain linear encodings. …”
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Fast quantitative susceptibility mapping with L1-regularization and automatic parameter selection by Bilgic, Berkin, Fan, Audrey P., Polimeni, Jonathan R., Cauley, Stephen F., Bianciardi, Marta, Adalsteinsson, Elfar, Setsompop, Kawin, Wald, Lawrence

“…Methods ℓ[subscript 1]-Regularized susceptibility mapping is accelerated by variable splitting, which allows closed-form evaluation of each iteration of the algorithm by soft thresholding and fast Fourier transforms. …”
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Abnormal event detection in crowded scenes using sparse representation by Cong, Yang, Yuan, Junsong, Liu, Ji

“…Observing that the group sparsity also implies a low rank structure, we reformulate the problem using matrix decomposition, which can handle large scale training samples by reducing the memory requirement at each iteration from O(k2) to O(k) where k is the number of samples. …”
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QoS-driven optimized design-based integrated visible light communication and positioning for indoor IoT networks by Yang, Helin, Zhong, Wen-De, Chen, Chen, Alphones, Arokiaswami, Du, Pengfei

“…As the network consists of multiple VLC access points (APs), we propose jointly optimizing the AP selection, bandwidth allocation, adaptive modulation, and power allocation approach to satisfy different QoS requirements of indoor devices while maximizing the network data rate. A low-complexity iterative algorithm is presented to solve the resource management (RM) optimization problem by decomposing it into two subproblems. …”
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Joint auction-coalition formation framework for communication-efficient federated learning in UAV-enabled Internet of Vehicles by Ng, Jer Shyuan, Lim, Bryan Wei Yang, Dai, Hong-Ning, Xiong, Zehui, Huang, Jianqiang, Niyato, Dusit, Hua, Xian-Sheng, Leung, Cyril, Miao, Chunyan

“…However, a single UAV may not have sufficient resources to provide services for all iterations of the FL process. In this paper, we present a joint auction-coalition formation framework to solve the allocation of UAV coalitions to groups of IoV components. …”
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Intelligent optimization of bioleaching process for waste lithium-ion batteries : an application of support vector regression approach by Ruhatiya, C., Gandra, R., Kondaiah, P., Manivas, K., Samhith, A., Gao, L., Lam, Jasmine Siu Lee, Garg, A.

“…The model employed is stable and efficient, reaching a stable optimized value under 300 iterations. The optimized input parameters values obtained are 144.39 g/L, 1.29% v/v, 6.70, 1513.05 ppm, 4989.79 ppm, 2094.22 ppm, 347.57 ppm and 2.37 for sucrose concentration, inoculum size, initial pH, oxalic acid, gluconic acid, malic acid, citric acid concentration and final pH, respectively.…”
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A global crowdsourcing open call to improve research mentorship in low- and middle-income countries: a mixed methods analysis by Oppong, Emmanuela, Bao, Huanyu, Tang, Weiming, Mejia, María I. Echavarria, Glozah, Franklin, Asanga, Nsisong, Boinett, Christine J., Aguilar, Ana M., Valido, Ezra, Lestari, Trisasi, Tucker, Joseph D.

“…Facilitation involves iterative cycles of planning, communication, and skill improvement. …”
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Accelerating computations in two-stage Bayesian system identification with Fisher information matrix and eigenvalue sensitivity by Zhu, Jia-Xin, Zhu, Zuo, Au, Siu-Kui

“…Exploiting the mathematical structure of the measure-of-fit function in the two-stage problem, this work proposes a Fisher scoring method for determining the MPV, where the Hessian matrix in a Newton’s iteration is replaced by the Fisher information matrix to eliminate repeated computations of second order derivatives and to improve con-vergence robustness. …”
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Utility distribution matters: enabling fast belief propagation for multi-agent optimization with dense local utility function by Deng, Yanchen, An, Bo

“…That is, we integrate both search and pruning to iteratively reduce the search space. Besides, we propose a discretization mechanism to offer a tradeoff between the reconstruction overhead and the pruning efficiency. …”
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RHONN modelling-enabled nonlinear predictive control for lateral dynamics stabilization of an in-wheel motor driven vehicle by Chen, Hao, Zhang, Junzhi, Lv, Chen

“…Based on the RHONN model, the steady-state responses of vehicle's yaw rate and sideslip angle are iteratively optimized and set as the control objectives for low-level controller, aiming to improve the system robustness. …”
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Enhancing federated learning with spectrum allocation optimization and device selection by Zhang, Tinghao, Lam, Kwok-Yan, Zhao, Jun, Li, Feng, Han, Huimei, Norziana Jamil

“…Due to practical considerations, FL selects a portion of devices to participate in the model training process at each iteration. Therefore, the tasks of efficient resource management and device selection will have a significant impact on the practical uses of FL. …”
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Learning feature embedding refiner for solving vehicle routing problems by Li, Jingwen, Ma, Yining, Cao, Zhiguang, Wu, Yaoxin, Song, Wen, Zhang, Jie, Chee, Yeow Meng

“…To this end, our FER allows current neural construction methods to not only iteratively refine the feature embeddings for boarder search range but also dynamically update the probability distributions for more diverse search. …”
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