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Now showing items 11-20 of 23
Machine learning to predict junction temperature based on optical characteristics in solid-state lighting devices: A test on WLEDs
(MDPI, 2022-08)
While junction temperature control is an indispensable part of having reliable solid-state lighting, there is no direct method to measure its quantity. Among various methods, temperature-sensitive optical parameter-based ...
On the use of machine learning for predicting defect fix time violations
(Science and Technology Publications, 2022)
Accurate prediction of defect fix time is important for estimating and coordinating software maintenance efforts. Likewise, it is useful to predict whether or not the initially estimated defect fix time will be exceeded ...
DiBLIoT: A distributed blacklisting protocol for iot device classification using the hashgraph consensus algorithm
(IEEE Computer Society, 2022)
Industrial applications require highly reliable, secure, low-power and low-delay communications. However, wireless communication links in the industrial environment suffer from various channel impairments which can compromise ...
Disentangling human trafficking types and the identification of pathways to forced labor and sex: an explainable analytics approach
(Springer, 2023-07)
Terms such as human trafficking and modern-day slavery are ephemeral but reflect manifestations of oppression, servitude, and captivity that perpetually have threatened the basic right of all humans. Operations research ...
Land subsidence susceptibility mapping using interferometric synthetic aperture radar (InSAR) and machine learning models in a semiarid region of iran
(MDPI, 2023-04)
Most published studies identify groundwater extraction as the leading cause of land subsidence (LS). However, the causes of LS are not only attributable to groundwater extraction. Other land-use practices can also affect ...
Comparative study of credit risk evaluation for unbalanced datasets using deep learning classifiers
(IEEE, 2023)
Credit risk assessment deals with calculating the risk of a loan not being repaid. For this reason, a lot of research effort is directed at credit risk analysis. In this study, machine learning models such as Light ...
Advancing home healthcare through machine learning: Predicting service time for enhanced patient care
(IEEE, 2023)
Providing healthcare services at home is crucial for patients who require long-term care or face mobility or other health-related constraints that prevent them from traveling to healthcare facilities. Effective data analysis ...
Feature extraction for enhancing data-driven urban building energy models
(European Council on Computing in Construction (EC3), 2023)
Building energy demand assessment plays a crucial role in designing energy-efficient building stocks. However, most studies adopting a data-driven approach feel the deficiency of datasets with building-specific information ...
A new era of modeling MOF-based membranes: Cooperation of theory and data science
(Wiley, 2024-01)
Membrane-based separation can offer significant energy savings over conventional separation methods. Given their highly customizable and porous structures, metal–organic frameworks- (MOFs) are considered as next-generation ...
Simulation of vehicles’ gap acceptance decision at unsignalized intersections using SUMO
(Elsevier, 2022)
In this paper, an artificial neural network (ANN)-based gap acceptance behavior model was proposed. The feasibility of implementing this model in a microscopic simulation tool was tested using the application programming ...
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