Zobrazeno 1 - 10
of 64
pro vyhledávání: '"Mye M. Sohn"'
Publikováno v:
The Journal of Supercomputing. 77:9780-9809
Data and information produced in network-centric environments are large and heterogeneous. As a solution to this challenge, ontology-based situation awareness (SA) is gaining attention because ontologies can contribute to the integration of heterogen
Publikováno v:
International Journal of Machine Learning and Computing. 10:735-739
Publikováno v:
World Wide Web. 24:1003-1025
Nowadays, many people use social media to communicate with others, share their interests and obtain information. As the performance of the embedded cameras on mobile phones improve, image-sharing social media became a popular tool for people to commu
Publikováno v:
Journal of the Korea Management Engineers Society. 25:117-135
Publikováno v:
The Journal of Korean Institute of Communications and Information Sciences. 45:418-427
Publikováno v:
IEEE Access, Vol 8, Pp 69359-69367 (2020)
In this paper, we propose an energy-saving framework for Wireless Sensor Networks (WSN) using machine learning techniques and meta-heuristics according to environmental states. Unlike conventional topology-based energy-saving methods, we focus on the
Publikováno v:
IEEE Access, Vol 8, Pp 97632-97642 (2020)
In this paper, we analyze a queueing system under the dyadic server control, workload control and delivery deadlines of data blocks. From the viewpoint of efficient power management for the wireless interface of a smart mobile device, we first focus
Publikováno v:
BigComp
Synonym identification is the key factor for ontology alignment. There are several researches which proposed synonym identification methods. However, most of the researches focus on the words in general contexts, which occurs the problem in finding s
Publikováno v:
The Journal of Supercomputing. 76:8003-8020
In this paper, we propose a novel approach that can recognize transition activities (e.g., turn to left or right, stand up, and travel down the stairs). Unlike simple activities, the transition activities have unique characteristics that change conti
Publikováno v:
Multimedia Tools and Applications. 78:4417-4435
In this paper, we propose an anomaly detection system of machines using a hybrid learning mechanism that combines two kinds of machine learning approaches, namely unsupervised and non-parametric learning. To do so, we used vibration data, which is kn