Results 51 to 60 of about 84,444 (264)

Artificial Intelligence for IT Operations–Based Performance Optimization in Desktop Virtualization

Electrica
Gradient Boosting and XGBoost achieved the lowest root mean squared error (RMSE, ≤ 3.9 MHz) and the highest R-squared (R², ≥ 0.74), whereas SVR and KNN underperformed, likely due to data sparsity and high dimensionality.
Mehmet Akif Özdemir, Hikmetcan Özcan
doaj   +1 more source

Comparative Study of Predicting the Molecular Diffusion Coefficient for Polar and Non-polar Binary Gas Using Neural Networks and Multiple Linear Regressions [PDF]

Kemija u Industriji, 2019
In the current study, an artificial neural network (ANN) and multiple linear regressions (MLR) have been used to develop predictive models for the estimation of molecular diffusion coefficients of 1252 polar and non-polar binary gases at multiple ...
Naima Melzi, Latifa Khaouane, Yamina Ammi, Salah Hanini, Maamar Laidi, Hamid Zentou   +5 more
doaj   +1 more source

Potential root mean square error skill score

Journal of Renewable and Sustainable Energy
Consistency, in a narrow sense, denotes the alignment between the forecast-optimization strategy and the verification directive. The current recommended deterministic solar forecast verification practice is to report the skill score based on root mean square error (RMSE), which would violate the notion of consistency if the forecasts are optimized ...
Martin János Mayer, Dazhi Yang
openaire   +3 more sources

Sudden anaerobization in Amphibacillus xylanus increases intracellular labile ferrous iron and inhibits cell growth

FEBS Open Bio, EarlyView.
Abruptly changing from aerobic to anaerobic conditions (sudden anaerobization) induced growth inhibition and a significant increase in intracellular labile ferrous iron in the aerotolerant anaerobe Amphibacillus xylanus. We found that free flavins mediate efficient electron transfer from NADH to ferric iron under anaerobic conditions, suggesting that ...
Shinya Kimata, Yoichi Sakai, Keisuke Tanaka, Etsuro Yoshimura, Ken Kitano, Morio Ishikawa, Tadahiro Nakamoto, Tsutomu Takayama, Hirofumi Inoue, Kaho Nomura, Tomonori Suzuki, Masataka Uchino, Akira Abe, Youichi Niimura   +13 more
wiley   +1 more source

Cricket performance predictions: a comparative analysis of machine learning models for predicting cricket player’s performance in the One Day International (ODI) world cup 2023

Здоров’я, спорт, реабілітація
Background and purpose Cricket, a globally renowned bat and ball sport, is the second most popular sport worldwide. The objective of the study is to utilize machine learning algorithms to predict the performance probabilities of Indian cricket ...
Swamynathan Sanjaykumar, Karthikeyan Udaichi, Gowtham Rajendiran, Marian Cretu, Zhanneta Kozina   +4 more
doaj   +1 more source

Vertical wind speed extrapolation using statistical approaches [PDF]

FME Transactions
The wind power industry has experienced a significant increase and popularity in recent times, and the latest statistics indicate that this sector is still thriving.
Nuha Hilal H., Balghonaim Adil, Pahlevi Rizka Reza, Rehman S., Mohandes M.   +4 more
doaj   +1 more source

Time‐restricted feeding prior to Mycobacterium tuberculosis infection reduces tissue CD4+ T cells with limited impact on bacterial clearance

FEBS Open Bio, EarlyView.
Time‐restricted feeding (TRF) in mice increased liver fatty acid oxidation and decreased fatty acid biosynthesis. These alterations persisted when TRF was discontinued and the host was infected with Mycobacterium tuberculosis. Pre‐exposure to TRF did not alter tissue (lung and spleen) mycobacterial burden but significantly reduced CD3+ T cells in lungs
Ashish Gupta, Nidhi Yadav, Subhasmita Das, R. Rajendra Kumar Reddy, Nupur Sharma, Amol Ratnakar Suryawanshi, Jaswinder Singh Maras, Ranjan Kumar Nanda   +7 more
wiley   +1 more source

Using artificial intelligence for wind speed prediction [PDF]

E3S Web of Conferences
Accurate wind speed prediction is critical for renewable energy management, agriculture, and weather forecasting. This study investigates the use of machine learning techniques for predicting daily average wind speed using meteorological features ...
Omari Asem, Alazzam Azmi, Badreddine Said, Abu Sharkh Hani, Alazzam Yasmeen, Bani Mustafa Ahmed, Al Alawi Roudha   +6 more
doaj   +1 more source

The crystal structure of the Borrelia burgdorferi nicotinamidase BBE22 resolves a long‐standing annotation error

FEBS Open Bio, EarlyView.
The crystal structure of Borrelia burgdorferi nicotinamidase (PncA/BBE22) reveals the correct full‐length protein initiated from a non‐canonical AUU start codon. The structure validates previous biochemical findings and resolves a long‐standing annotation error, demonstrating that the truncated database sequence is structurally incompatible with the ...
Kalvis Brangulis
wiley   +1 more source

Quantum root-mean-square error and measurement uncertainty relations

, 2013
This second version has been substantially edited to ensure a balanced comparison of the two proposed quantum generalizations of the Gauss rms error concept.
Busch, Paul, Lahti, Pekka, Werner, Reinhard F   +2 more
openaire   +2 more sources