Results 61 to 70 of about 93,376 (303)
Time Series Forecasting for Touristic Policies
Computer Sciences & Mathematics ForumThe formulation of touristic policies is a time-consuming process that consists of a wide range of steps and procedures. These policies are highly dependent on the number of tourists and visitors to an area to be as effective as possible.
Konstantinos Mavrogiorgos +5 more
doaj +1 more source
Molecular Oncology, EarlyView.Keratin 19 (KRT19) is overexpressed in high‐grade serous ovarian cancer with high levels of Kallikrein‐related peptidases (KLK) 4–7 and is associated with poor survival. In vivo analyses demonstrate that elevated KRT19 increases peritoneal tumour burden.
Sophia Bielesch +13 more
wiley +1 more source
Time series forecasting methods in emergency contexts
Scientific Reports, 2023 The key issues in any fire emergency are recognising fire hotspots, locating the emergency intervention team (EI), following the evolution of the fire, and selecting the evacuation path.
P. Villoria Hernandez +4 more
doaj +1 more source
Molecular Oncology, EarlyView.We have established a humanized orthotopic patient‐derived xenograft (Hu‐oPDX) mouse model of high‐grade serous ovarian cancer (HGSOC) that recapitulates human tumor–immune interactions. Using combined anti‐PD‐L1/anti‐CD73 immunotherapy, we demonstrate the model's improved biological relevance and enhanced translational value for preclinical ...
Luka Tandaric +10 more
wiley +1 more source
CCDC80 suppresses high‐grade serous ovarian cancer migration via negative regulation of B7‐H3
Molecular Oncology, EarlyView.PAX8 is a lineage‐specific master regulator of transcription in high‐grade serous ovarian cancer (HGSC) progression. We show for the first time that PAX8 facilitates proliferation and metastasis by repressing the cell autonomous tumor suppressor CCDC80 and inducing B7‐H3 expression.
Aya Saleh +12 more
wiley +1 more source
Seasonal Time Series Forecasting by F1-Fuzzy Transform
Sensors, 2019 We present a new seasonal forecasting method based on F1-transform (fuzzy transform of order 1) applied on weather datasets. The objective of this research is to improve the performances of the fuzzy transform-based prediction method applied to seasonal ...
Ferdinando Di Martino, Salvatore Sessa
doaj +1 more source
Forecasting Time Series from Clusters. [PDF]
Forecasting large numbers of time series is a costly and time-consuming exercise. Before forecasting a large number of series that are logically connected in some way, the authors can first cluster them into groups of similar series.
Inder, B., Marahaj, E.A.
core
Molecular Oncology, EarlyView.Both cg12821679MAPRE3 methylation and MAPRE3 expression are significantly associated with overall survival (OS) of non‐small cell lung cancer. Meanwhile, MAPRE3 expression significantly modified the effect of smoking cessation on OS. Smoking cessation benefits OS merely for patients with high MAPRE3 expression.
Chao Chen +14 more
wiley +1 more source
Forecasting Canadian Time Series With the New-Keynesian Model [PDF]
This paper documents the out-of-sample forecasting accuracy of the New Keynesian Model for Canada. We estimate our variant of the model on a series of rolling subsamples, computing out-of-sample forecasts one to eight quarters ahead at each step.
Kevin Moran, Mohamed Gammoudi, Ali Dib
core +2 more sources
, 2020 Time series forecasting is an important area of machine learning that is often neglected. The topic is relevant nowadays because there are so many prediction problems that involve a time component. These problems are neglected because it is this time component that makes time series problems more difficult to handle.
openaire +2 more sources