Results 71 to 80 of about 692,395 (345)

Multi-Group Fairness Evaluation via Conditional Value-at-Risk Testing [PDF]

, 2023
Lucas Monteiro Paes, Ananda Theertha Suresh, Alex Beutel, Flávio P. Calmon, Ahmad Beirami   +4 more
openalex   +1 more source

Metronidazole‐Loaded Cyclodextrin Nanogels for Antibacterial Therapy and Microbiota Regulation in Periodontitis

Advanced Healthcare Materials, EarlyView.
A methacrylamide β‐cyclodextrin‐based nanogel (MACD nGel) is developed to load the antimicrobial drug Metronidazole (MNZ) for topical delivery for the treatment of periodontitis. It is demonstrated that cyclodextrin nanogel (nGel) loaded with metronidazole provides an efficient drug delivery route but also has potential clinical applications and offers
Yanjing Ji, Ruichen Zhang, Dongyi Xu, Patrick C. A. van der Wel, Alessia Lasorsa, Guotai Li, Fangze Guo, Qihui Zhou, Patrick van Rijn   +8 more
wiley   +1 more source

Value-at-Risk and Conditional Value-at-Risk Minimization for Hazardous Materials Routing [PDF]

, 2013
This chapter provides fundamentals of value-at-risk and conditional value-at-risk models applied to routing problems in hazardous materials transportation.
Toumazis, Iakovos, Kwon, Changhyun, Batta, Rajan   +2 more
openaire   +1 more source

Physical Intelligence in Small‐Scale Robots and Machines

Advanced Materials, EarlyView.
“Physical intelligence” (PI) empowers biological organisms and artificial machines, especially at the small scales, to perceive, adapt, and even reshape their complex, dynamic, and unstructured operation environments. This review summarizes recent milestones and future directions of PI in small‐scale robots and machines.
Huyue Chen, Metin Sitti
wiley   +1 more source

Programmable Dimensional Lithography with Digital Micromirror Devices for Multifunctional Microarchitectures

Advanced Materials Technologies, EarlyView.
This review explores recent advances in digital micromirror device (DMD)‐based lithography, focusing on its programmable light modulation, multi‐material compatibility, and dimensional patterning strategies. It highlights innovations from optical system design to materials integration and multifunctional applications, positioning DMD lithography as a ...
Yubin Lee, Byungcheon Yoo, Chaeyeong Ryu, Jongwon Oh, Dahye Baek, Jiseok Lee   +5 more
wiley   +1 more source

PERHITUNGAN VALUE AT RISK DENGAN PENDEKATAN THRESHOLD AUTOREGRESSIVE CONDITIONAL HETEROSCEDASTICITY-GENERALIZED EXTREME VALUE

Media Statistika, 2019
Stock is the most popular type of financial asset investment. Before buying a stock, an investor must estimate the risks which will be received. Value at Risk (VaR) is one of the methods that can be used to measure the level of risk.
Mutik Dian Prabaning Tyas, Di Asih I Maruddani, Rita Rahmawati   +2 more
doaj   +1 more source

Stable Imitation of Multigait and Bipedal Motions for Quadrupedal Robots Over Uneven Terrains

Advanced Robotics Research, EarlyView.
How are quadrupedal robots empowered to execute complex navigation tasks, including multigait and bipedal motions? Challenges in stability and real‐world adaptation persist, especially with uneven terrains and disturbances. This article presents an imitation learning framework that enhances adaptability and robustness by incorporating long short‐term ...
Erdong Xiao, Yinzhao Dong, Ji Ma, Peng Lu   +3 more
wiley   +1 more source

Do Nonparametric Measures of Extreme Equity Risk Change the Parametric Ordinal Ranking? Evidence from Asia

Risks, 2018
There has been much discussion in the literature about how central measures of equity risk such as standard deviation fail to account for extreme tail risk of equities.
Robert J. Powell, Duc H. Vo, Thach N. Pham   +2 more
doaj   +1 more source

Risk-Aware Linear Quadratic Control Using Conditional Value-at-Risk [PDF]

, 2022
Masako Kishida, Ahmet Cetinkaya
openalex   +1 more source

Continual Learning for Multimodal Data Fusion of a Soft Gripper

Advanced Robotics Research, EarlyView.
Models trained on a single data modality often struggle to generalize when exposed to a different modality. This work introduces a continual learning algorithm capable of incrementally learning different data modalities by leveraging both class‐incremental and domain‐incremental learning scenarios in an artificial environment where labeled data is ...
Nilay Kushawaha, Egidio Falotico
wiley   +1 more source