Zobrazeno 1 - 10
of 244
pro vyhledávání: '"Mehrdad Nourani"'
Publikováno v:
BMC Bioinformatics, Vol 21, Iss S4, Pp 1-16 (2020)
Abstract Background Identifying drug-target interaction is a key element in drug discovery. In silico prediction of drug-target interaction can speed up the process of identifying unknown interactions between drugs and target proteins. In recent stud
Externí odkaz:
https://doaj.org/article/b7d584b2c9a7431ea4228b0aaddd078a
Autor:
Yong-Jun Shin, Mehrdad Nourani
Publikováno v:
PLoS ONE, Vol 5, Iss 2, p e9376 (2010)
State diagrams (stategraphs) are suitable for describing the behavior of dynamic systems. However, when they are used to model large and complex systems, determining the states and transitions among them can be overwhelming, due to their flat, unstra
Externí odkaz:
https://doaj.org/article/5fc1fb2af0f5443aa28fa780ffa94329
Publikováno v:
2022 IEEE 22nd International Conference on Bioinformatics and Bioengineering (BIBE).
Publikováno v:
2021 IEEE Biomedical Circuits and Systems Conference (BioCAS).
Autor:
Mehrdad Nourani, Seyyed MohammadSaleh Hosseini, Munawara Saiyara Munia, Jay Harvey, Hina Dave
Publikováno v:
ICHI
Epilepsy is a socially-stigmatizing chronic neurological condition. Limited availability of seizure Electroencephalogram (EEG) data makes the application of machine learning techniques for epileptic seizure detection very challenging. In this work, a
Publikováno v:
BHI
This work outlines a method for patient ambulation assessment based on tracking the human body using a depth camera. To classify static postures and dynamic movements, a hierarchical classifier is proposed. By analyzing the relative positions of the
Publikováno v:
IEEE Transactions on Energy Conversion. 34:761-772
This paper presents a generic analytical tool to diagnose and classify faults in permanent magnet synchronous motors. The proposed method deploys wavelet transform to extract features for fault diagnosis, which provides a framework for studying nonst
Electromyography is a promising approach to the gesture recognition of humans if an efficient classifier with high accuracy is available. In this paper, we propose to utilize Extreme Value Machine (EVM) as a high-performance algorithm for the classif
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::9da1f79a5412c4091f4f50d46a3c3191
In recent years, real-time control of prosthetic hands has gained a great deal of attention. In particular, real-time analysis of Electromyography (EMG) signals has several challenges to achieve an acceptable accuracy and execution delay. In this pap
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::0c5acaede24f97555aeee3fb4f5557fe
Publikováno v:
ICHI
This paper presents our patient activity monitoring system (PAMS), which combines a wrist-worn device and a real-time location system (RTLS) with active tags. Four main data streams were used: location coordinates, 3D accelerometer, heart rate, and e