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Using neurocomputing techniques to determine microstructural properties in a Li-ion battery. Neural Comput Appl 2022. [DOI: 10.1007/s00521-022-06985-0] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/19/2022]
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Using Patent Technology Networks to Observe Neurocomputing Technology Hotspots and Development Trends. SUSTAINABILITY 2020. [DOI: 10.3390/su12187696] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
In recent years, development in the fields of big data and artificial intelligence has given rise to interest among scholars in neurocomputing-related applications. Neurocomputing has relatively widespread applications because it is a critical technology in numerous fields. However, most studies on neurocomputing have focused on improving related algorithms or application fields; they have failed to highlight the main technology hotspots and development trends from a comprehensive viewpoint. To fill the research gap, this study adopts a new viewpoint and employs technological fields as its main subject. Neurocomputing patents are subjected to network analysis to construct a neurocomputing technology hotspot. The results reveal that the neurocomputing technology hotspots are algorithms, methods or devices for reading or recognizing printed or written characters or patterns, and digital storage characterized by the use of particular electric or magnetic storage elements. Furthermore, the technology hotspots are discovered to not be clustered around particular fields but, rather, are multidisciplinary. The applications that combine neurocomputing with digital storage are currently undergoing the most extensive development. Finally, patentee analysis reveal that neurocomputing technology is mainly being developed by information technology corporations, thereby indicating the market development potential of neurocomputing technology. This study constructs a technology hotspot network model to elucidate the trend in development of neurocomputing technology, and the findings may serve as a reference for industries planning to promote emerging technologies.
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Mozaffari SH, Srinivasan S, Saghir MZ. A Study on Thermodiffusion in Ternary Liquid Mixtures Using Enhanced Molecular Dynamics Algorithm with Experimental Validation. CAN J CHEM ENG 2019. [DOI: 10.1002/cjce.23199] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/26/2022]
Affiliation(s)
- Seyedeh Hoda Mozaffari
- Department of Mech. & Indust. EngineeringRyerson University350 Victoria St.TorontoON, M5B 2K3Canada
| | - Seshasai Srinivasan
- Department of Mech. & Indust. EngineeringRyerson University350 Victoria St.TorontoON, M5B 2K3Canada
- W Booth School of Engineering Pract. & Tech., 1280 Main St. WestMcMaster UniversityHamiltonON, L8S 4L8Canada
- Department of Mech. EngineeringMcMaster UniversityHamiltonON, L8S 4L8Canada
| | - M. Ziad Saghir
- Department of Mech. & Indust. EngineeringRyerson University350 Victoria St.TorontoON, M5B 2K3Canada
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Predicting thermodiffusion in an arbitrary binary liquid hydrocarbon mixtures using artificial neural networks. Neural Comput Appl 2014. [DOI: 10.1007/s00521-014-1603-3] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/25/2022]
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