Results 51 to 60 of about 1,047,164 (269)

Measuring Statistical Asymmetries of Stochastic Processes: Study of the Autoregressive Process

Entropy, 2018
We use the definition of statistical symmetry as the invariance of a probability distribution under a given transformation and apply the concept to the underlying probability distribution of stochastic processes.
Arthur Matsuo Yamashita Rios de Sousa, Hideki Takayasu, Misako Takayasu   +2 more
doaj   +1 more source

Forecasting Wholesale Electricity Market Prices Considering Bidding Conditions Using Price Sensitivity

Advanced Energy and Sustainability Research, EarlyView.
It is very difficult to predict spot prices in Japan, where solar power generation has entered the market. Herein, It is attempted to predict the timing of sudden price changes by using price sensitivity, which will begin to be made public in 2021. The impact of price sensitivity on forecasting will be examined by making other variables general.
Shinji Hirota, Jindan Cui, Xue Fang, Takashi Oozeki, Yuzuru Ueda   +4 more
wiley   +1 more source

Product differentiation in the fruit industry: Lessons from trademarked apples

Agribusiness, EarlyView.
Abstract We derive price premiums for patented or trademarked apple varieties, also known as “club apples,” compared to open‐variety apples. We use an expansive retail scanner dataset, along with unique data on apple taste characteristics, to estimate monthly club apple premiums for 2008–2018.
Modhurima Dey Amin, Syed Badruddoza, Jill J. McCluskey, Gregory Astill   +3 more
wiley   +1 more source

A comparison of multiband and multiband multiecho gradient‐echo EPI for task fMRI at 3 T

Human Brain Mapping, Volume 44, Issue 1, Page 82-93, January 2023., 2023
In summary, we found that multiband multiecho (MBME) and MB give a comparable performance in most brain regions with this comparison study. In the regions with dropouts and susceptibility induced inhomogeneity, MBME performed somewhat better at the group level.
Zahra Fazal, Daniel E. P. Gomez, Alberto Llera, José P. R. F. Marques, Thomas Beck, Benedikt A. Poser, David G. Norris   +6 more
wiley   +1 more source

Non-Autoregressive Machine Translation with Latent Alignments [PDF]

arXiv, 2020
This paper presents two strong methods, CTC and Imputer, for non-autoregressive machine translation that model latent alignments with dynamic programming. We revisit CTC for machine translation and demonstrate that a simple CTC model can achieve state-of-the-art for single-step non-autoregressive machine translation, contrary to what prior work ...
arxiv  

Volatility analysis and forecasting of vegetable prices using an ARMA‐GARCH model: An application of the CF filter and seasonal adjustment method to Korean green onions

Agribusiness, EarlyView.
Abstract The vegetable market experiences significant price fluctuations due to the complex interplay of trend, cyclical, seasonal, and irregular factors. This study takes Korean green onions as an example and employs the Christiano–Fitzgerald filter and the CensusX‐13 seasonal adjustment methods to decompose its price into four components: trend ...
Yiyang Qiao, Byeong‐il Ahn
wiley   +1 more source

RETRACTED: Artificial intelligence for emergency medical care

Health Care Science, EarlyView., 2023
‘Applications of artificial intelligence in emergency medical service’. Abstract There is increasing research into the potential benefits of incorporating artificial intelligence (AI) and machine learning algorithms into emergency medical services. AI is finding new applications across a wide range of sectors, one of which is healthcare, where it is ...
Shivam Rajput, Pramod Kumar Sharma, Rishabha Malviya   +2 more
wiley   +1 more source

Selection of Temporal Lags for Predicting Riverflow Series from Hydroelectric Plants Using Variable Selection Methods

Energies, 2020
The forecasting of monthly seasonal streamflow time series is an important issue for countries where hydroelectric plants contribute significantly to electric power generation.
Hugo Siqueira, Mariana Macedo, Yara de Souza Tadano, Thiago Antonini Alves, Sergio L. Stevan, Domingos S. Oliveira, Manoel H.N. Marinho, Paulo S.G. de Mattos Neto,  João F. L. de Oliveira, Ivette Luna, Marcos de Almeida Leone Filho, Leonie Asfora Sarubbo, Attilio Converti   +12 more
doaj   +1 more source

Deep Encoder, Shallow Decoder: Reevaluating Non-autoregressive Machine Translation [PDF]

arXiv, 2020
Much recent effort has been invested in non-autoregressive neural machine translation, which appears to be an efficient alternative to state-of-the-art autoregressive machine translation on modern GPUs. In contrast to the latter, where generation is sequential, the former allows generation to be parallelized across target token positions.
arxiv  

Video Prediction by Efficient Transformers [PDF]

arXiv, 2022
Video prediction is a challenging computer vision task that has a wide range of applications. In this work, we present a new family of Transformer-based models for video prediction. Firstly, an efficient local spatial-temporal separation attention mechanism is proposed to reduce the complexity of standard Transformers. Then, a full autoregressive model,
arxiv