Machine learning aided bio-oil production with high energy recovery and low nitrogen content from hydrothermal liquefaction of biomass with experiment verification

J Li, W Zhang, T Liu, L Yang, H Li, H Peng… - Chemical Engineering …, 2021 - Elsevier
Hydrothermal liquefaction (HTL) of biomass with high moisture (eg, algae, sludge, manure,
and food waste) is a promising and sustainable approach to produce renewable energy (bio …

[HTML][HTML] Self-learning algorithm to predict indoor temperature and cooling demand from smart WiFi thermostat in a residential building

K Huang, KP Hallinan, R Lou, A Alanezi, S Alshatshati… - Sustainability, 2020 - mdpi.com
Smart WiFi thermostats have moved well beyond the function they were originally designed
for; namely, controlling heating and cooling comfort in buildings. They are now also learning …

Prediction of drug amount in Parkinson's disease using hybrid machine learning systems and radiomics features

MR Salmanpour, M Hosseinzadeh… - … Journal of Imaging …, 2023 - Wiley Online Library
Parkinson's disease (PD) is progressive and heterogeneous. Levodopa is widely prescribed
to control PD, and its long‐term‐treatment leads to dyskinesia in a dose‐dependent manner …

Application of novel hybrid machine learning systems and radiomics features for non-motor outcome prediction in Parkinson's disease

MR Salmanpour, M Bakhtiyari… - Physics in Medicine …, 2023 - iopscience.iop.org
Objectives. Parkinson's disease (PD) is a complex neurodegenerative disorder, affecting 2%–
3% of the elderly population. Montreal Cognitive Assessment (MoCA), a rapid nonmotor …

Estimating smart Wi-Fi thermostat-enabled thermal comfort control savings for any residence

AD Alhamayani, Q Sun, KP Hallinan - Clean Technologies, 2021 - mdpi.com
Nowadays, most indoor cooling control strategies are based solely on the dry-bulb
temperature, which is not close to a guarantee of thermal comfort of occupants. Prior …

[HTML][HTML] An Improved Method to Estimate Savings from Thermal Comfort Control in Residences from Smart Wi-Fi Thermostat Data

AD Alhamayani, Q Sun, KP Hallinan - Clean Technologies, 2022 - mdpi.com
The net-zero global carbon target for 2050 needs both expansion of renewable energy and
substantive energy consumption reduction. Many of the solutions needed are expensive …

Iterative decorrelation analysis, unit of measure preserving transformations and latent biomarker discovery

JG Tamez-Peña - 2023 - researchsquare.com
Background Numerous biomarker discovery studies and exploratory clinical studies extract
a large set of measurable variables, which often have varying degrees of correlation among …

[BOOK][B] Data Mining For Residential Buildings Using Smart WiFi Thermostats

K Huang - 2021 - search.proquest.com
Smart WiFi thermostats are not just a device for controlling heating and cooling comfort in
buildings, they also can learn from occupant behaviors and permit occupants to control their …

On the Utility of Ordered Incremental Attribute Learning based Variance and mRMR Techniques

S Gorrab, FB Rejab, K Nouira - 2023 - researchsquare.com
From the major issues of machine learning and data mining is Feature Selection, picking
only the pertinent features to further emphasize the learning search. One relaxed category of …

[BOOK][B] Smart WI-FI Thermostat-enabled Thermal Comfort Control Saving For Any Residence Using Long-Short Term Memory

AD Alhamayani - 2022 - search.proquest.com
Indoor thermal comfort in residential buildings can not only represented by internal
temperature; other factors can affect the thermal satisfaction, such as relative humidity and …