Zobrazeno 1 - 10
of 705
pro vyhledávání: '"Vu, Linh"'
This paper introduces a novel convolutional neural networks (CNN) framework tailored for end-to-end audio deep learning models, presenting advancements in efficiency and explainability. By benchmarking experiments on three standard speech emotion rec
Externí odkaz:
http://arxiv.org/abs/2405.01815
Publikováno v:
Electric Power Systems Research, volume 229, pages 110191, year 2024
This paper presents an original energy management methodology to enhance the resilience of ship power systems. The integration of various energy storage systems (ESS), including battery energy storage systems (BESS) and super-capacitor energy storage
Externí odkaz:
http://arxiv.org/abs/2403.01102
Autor:
Anisa Rilla Lubis, Nguyen Vu Linh, Orranee Srinual, Camilla Maria Fontana, Khambou Tayyamath, Supreya Wannavijit, Punika Ninyamasiri, Toungporn Uttarotai, Wanaporn Tapingkae, Yuthana Phimolsiripol, Hien V. Van Doan
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-18 (2024)
Abstract This study explores the effects of dietary supplementation with passion fruit peel pectin (Passiflora edulis) and red yeast cell walls (Sporidiobolus pararoseus) on growth performance, immunity, intestinal morphology, gene expression, and gu
Externí odkaz:
https://doaj.org/article/44c72c6dacf94be19628a84aa9922da8
Publikováno v:
IEEE Transactions on Industry Applications, vol. 60, no. 2, pp. 2142-2152, March-April 2024
This paper presents a novel Cyber-Hardware-in-the-Loop (Cyber-HIL) platform for assessing control operation in ship cyber-physical systems. The proposed platform employs cutting-edge technologies, including Docker containers, real-time simulator $OPA
Externí odkaz:
http://arxiv.org/abs/2306.14017
This paper addresses the load restoration problem after power outage events. Our primary proposed methodology is using multi-agent deep reinforcement learning to optimize the load restoration process in distribution systems, modeled as networked micr
Externí odkaz:
http://arxiv.org/abs/2306.14018
Multi-dimensional classification (MDC) can be employed in a range of applications where one needs to predict multiple class variables for each given instance. Many existing MDC methods suffer from at least one of inaccuracy, scalability, limited use
Externí odkaz:
http://arxiv.org/abs/2306.06517
The fairness of machine learning-based decisions has become an increasingly important focus in the design of supervised machine learning methods. Most fairness approaches optimize a specified trade-off between performance measure(s) (e.g., accuracy,
Externí odkaz:
http://arxiv.org/abs/2301.13420
Autor:
Chinh Le Xuan, Vu Linh Nguyen, Supreya Wannavijit, Piyatida Outama, Nuttapon Khongdee, Nantaporn Sutthi, Viet Vuong Nguyen, Seyed Hossein Hoseinifar, Prapansak Srisapoome, Hien Van Doan
Publikováno v:
Journal of the World Aquaculture Society, Vol 55, Iss 5, Pp n/a-n/a (2024)
Abstract This study examines the use of dragon fruit peel (DFP) powder as a dietary supplement on growth performance, immune responses, and gene expression of Nile tilapia, Oreochromis niloticus, cultured within biofloc systems. A total of 300 Nile t
Externí odkaz:
https://doaj.org/article/d0d3928b29a64c64b1088557572daa9c
In this paper, we consider the problem of making skeptical inferences for the multi-label ranking problem. We assume that our uncertainty is described by a convex set of probabilities (i.e. a credal set), defined over the set of labels. Instead of le
Externí odkaz:
http://arxiv.org/abs/2210.08576