Browsing by Subject "Machine learning"
Now showing items 1-20 of 21
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Applying machine learning approach in recycling
(Springer Nature, 2021-02-17)Waste generation has been increasing drastically based on the world’s population and economic growth. This has signifcantly afected human health, natural life, and ecology. The utilization of limited natural resources, ... -
CGN-MPred: Cofunctional gene network-based mutation prediction from exposure conditions
(IEEE, 2021-12-09)The prediction of gene mutation of bacteria when exposed to different conditions is beneficial in the development of drugs and vaccines. However, the existing prediction models are suboptimal in their performance. In this ... -
Comparison of machine learning and deep learning models for network intrusion detection systems
(MDPI AG, 2020-09-30)The development of robust anomaly-based network detection systems, which are preferred over static signal-based network intrusion, is vital for cybersecurity. The development of a flexible and dynamic security system is ... -
Complex and entangled public policy: Here be dragons in Emergence, Entanglement, and Political Economy
(Springer, Cham, 2020-12-05)The tools and concepts of the emerging field of complexity science—like agent-based modeling, network theory, and machine learning—can offer powerful insights to economists and crafters of public policy. Complexity science ... -
Deep Learning–Based Advances
(Humana Press Inc., 2022-06-14)Posttranslational modification (PTM ) is a ubiquitous phenomenon in both eukaryotes and prokaryotes which gives rise to enormous proteomic diversity. PTM mostly comes in two flavors: covalent modification to polypeptide ... -
DeepQA: improving the estimation of single protein model quality with deep belief networks
(BioMed Central Ltd, 2016-12-05)Background: Protein quality assessment (QA) useful for ranking and selecting protein models has long been viewed as one of the major challenges for protein tertiary structure prediction. Especially, estimating the quality ... -
Health diagnostics using multi-attribute classification fusion
(Elsevier Ltd., 2014-06)This paper presents a classification fusion approach for health diagnostics that can leverage the strengths of multiple member classifiers to form a robust classification model. The developed approach consists of three ... -
Ibeaconmap: Automated indoor space representation for beacon-based wayfinding
(Springer, 2020-09)Traditionally, there have been few options for navigational aids for the blind and visually impaired (BVI) in large indoor spaces. Some recent indoor navigation systems allow users equipped with smartphones to interact ... -
Image analysis with machine learning algorithms to assist breast cancer treatment
(Springer, Cham, 2021-06-06)Real-time imaging technology has the potential to be applied to many complex surgical procedures such as those used in treating people with breast cancer. Key delaying factors for the successful development of real-time ... -
Image analysis with machine learning algorithms to assist breast cancer treatment
(Springer, Cham, 2021-06-06)Real-time imaging technology has the potential to be applied to many complex surgical procedures such as those used in treating people with breast cancer. Key delaying factors for the successful development of real-time ... -
Machine learning applied to programming quantum computers
(American Institute of Aeronautics and Astronautics, 2019-01-06)We apply machine learning to “program” quantum computers, both in simulation and in experimental hardware. A major difficulty in quantum computing is developing effective algorithms that can be programmed on a quantum ... -
Machine learning approach for truck-drones based last-mile delivery in the era of industry 4.0
(Elsevier Ltd, 2022-11-01)Under the vision of industry 4.0, the integration of drones in last-mile delivery can transform traditional delivery practices and provide competitive advantages. However, the combinatorial nature of the routing problem ... -
A machine-learning based approach to privacy-aware information-sharing in mobile social networks
(Elsevier B.V., 2016-01)Contextual information about users is increasingly shared on mobile social networks. Examples of such information include users' locations, events, activities, and the co-presence of others in proximity. When disclosing ... -
Prediction of airline delays based on machine learning algorithms
(Association for Information Systems, 2019)Every year around 20% of all flights are delayed or canceled. The costs of these events to the airline companies and passengers are in billions of dollars each year. According to a report published in 2010 by UC Berkeley, ... -
Solar power prediction in different forecasting horizons using machine learning and time series techniques
(IEEE, 2021-07-01)Solar power generation is highly intermittent, nonlinear, and variable in nature. The increase in penetration level of solar energy resources poses technical challenges. An accurate forecasting model is crucial to minimizing ... -
Structural-material-operational performance relationship for pool boiling on enhanced surfaces using deep neural network model
(Elsevier Ltd, 2022-12-01)An accurate predictive model of the enhanced pool boiling heat transfer on various surface modifications is essential to operate the pool boiling and design the optimal surface designs. However, the existing predictive ... -
Supervised machine learning approach for effective supplier classification
(IEEE, 2019-12)Supplier assessment plays a critical role in the supply chain management, which involves the flow of goods and services from the initial stage (raw material procurement) to the final stage (delivery). Supplier assessment ... -
A survey of biometric and machine learning methods for tracking students' attention and engagement
(IEEE, 2021-02-23)The skills of focusing and paying attention are critical to student learning. According to Piontkowski et al. [40], "Educators often talk about attention as a general mental state in which the mind focuses on some special ... -
A survey on machine and deep learning models for childhood and adolescent obesity
(IEEE, 2021-11-25)Childhood and adolescent obesity is a serious health problem that is on the rise at the global level. Earlier, certain diseases such as Type 2 diabetes, high blood pressure, and heart disease affected only adults, but now ... -
Utilizing Machine Learning to Predict Offshore Wind Farm Power Output for European Countries
(IEEE, 2022-10-25)One might assume that the types of energy resources used by a country and its level of development are related since developed nations focus on using alternative energy sources like the wind to produce green and sustainable ...