Results 101 to 110 of about 24,371,806 (309)

Mining Frequent Item Sets in Asynchronous Transactional Data Streams over Time Sensitive Sliding Windows Model [PDF]

Mehran University Research Journal of Engineering and Technology, 2016
EPs (Extracting Frequent Patterns) from the continuous transactional data streams is a challenging and critical task in some of the applications, such as web mining, data analysis and retail market, prediction and network monitoring, or analysis of ...
QAISAR JAVAID, FARIDA MEMON, SHAHNAWAZ TALPUR, MUHAMMAD ARIF, MUHAMMAD DAUD AWAN   +4 more
doaj  

Analysis on Improving the Response Time with PIDSARSA-RAL in ClowdFlows Mining Platform

EAI Endorsed Transactions on Energy Web, 2018
This paper provides an improved parallel data processing in Big Data mining using ClowdFlows platform. The big data processing involves an improvement in Proportional Integral Derivative (PID) controller using Reinforcement Adaptive Learning (RAL).
N. Yuvaraj, R. Arshath Raja, Dr. V. Ganesan, Dr. C. Suresh Gnana Dhas   +3 more
doaj   +1 more source

Fluorescent Hydrogel‐Based Strain Sensor With Machine Learning‐Augmented Performance

Advanced Intelligent Discovery, EarlyView.
Fluorescent hydrogel strain sensor based on carbon quantum dots enabling optical readout of deformation through strain‐dependent emission changes, coupled with Random Forest analysis to capture nonlinear fluorescence‐concentration relationships and identify optimal sensing conditions. Hydrogels are ideal matrices for bio‐integrated wearable sensors due
Tailai Chen, Tianlong Liu, Chao Lu, Rimsha Malik, Jin Zhang   +4 more
wiley   +1 more source

Mining association rules for the quality improvement of the production process [PDF]

, 2013
Academics and practitioners have a common interest in the continuing development of methods and computer applications that support or perform knowledge-intensive engineering tasks.
Rigal, Fabien, Kamsu-Foguem, Bernard, Mauget, Félix   +2 more
core   +1 more source

Constraint-based discriminative dimension selection for high-dimensional stream clustering

IJAIN (International Journal of Advances in Intelligent Informatics), 2018
Clustering data streams is one of active research topic in data mining. However, runtime of the existing stream clustering algorithms increases and their performance drop in the face of large number of dimensions.
Kitsana Waiyamai, Thanapat Kangkachit
doaj   +1 more source

From Data to Discovery: Machine Learning–Enabled Intelligent Characterization of Two‐Dimensional Materials

Advanced Intelligent Discovery, EarlyView.
Machine learning serves as a central engine for the intelligent characterization of two‐dimensional materials by integrating multimodal techniques, including optical microscopy, spectroscopy, electron microscopy, and scanning probe microscopy (SPM). This unified framework enables automated, high‐throughput, and quantitative extraction of structural ...
Zhi‐Long Cao, Jia‐Xu Yan
wiley   +1 more source

Application Of Data Mining [PDF]

, 2014
Knowledge and understanding of a problem is always the first step in identifying effective solutions.The application of data mining techniques on official data has great potential in supporting goodpublic policy. It is not straight forward and requires a
Singh, Prempratap; CSE department , Unique College Bhopal, Gosawi, Gouri; CSE department , Unique College Bhopal, Dubey, Sulakshana; CSE department , Unique College Bhopal   +2 more
core   +1 more source

A Framework for Dynamic User Modeling Integrating Data Stream Mining and Process Mining in Educational Contexts

IEEE Access
A user model (UM) is a representation of the characteristics, behaviors, and preferences of a user that a computer system utilizes to provide the user with personalized experiences.
Maria Yesenia Zavaleta-Sanchez, Edgard Benitez-Guerrero, Guillermo Gilberto Molero-Castillo, Carmen Mezura-Godoy, Luis Gerardo Montane-Jimenez   +4 more
doaj   +1 more source

Current Standards of Monitoring Models in Healthcare Settings

Advanced Intelligent Discovery, EarlyView.
AI/ML‐enabled medical devices are entering clinical practice faster than monitoring standards mature. This review highlights gaps in postmarket surveillance, limited use of predetermined change‐control plans, and the need for ongoing performance tracking, drift detection, explainability, and workflow‐aware governance to support safer, more reliable ...
Alan Kay, Daljit Takher, Wenting Liu, Emily Wittrup, Gilbert S. Omenn, Kayvan Najarian   +5 more
wiley   +1 more source

rEMM: Extensible Markov Model for Data Stream Clustering in R [PDF]

Clustering streams of continuously arriving data has become an important application of data mining in recent years and efficient algorithms have been proposed by several researchers. However, clustering alone neglects the fact that data in a data stream
Michael Hahsler, Margaret H. Dunham
core