Zobrazeno 1 - 10
of 72
pro vyhledávání: '"Songsiri P"'
Publikováno v:
International Journal of Applied Mathematics and Computer Science, Vol 28, Iss 4, Pp 705-717 (2018)
We propose new methods for support vector machines using a tree architecture for multi-class classification. In each node of the tree, we select an appropriate binary classifier, using entropy and generalization error estimation, then group the examp
Externí odkaz:
https://doaj.org/article/2bd093e86d234a9c98afe1bcb66b93fe
This paper considers joint learning of multiple sparse Granger graphical models to discover underlying common and differential Granger causality (GC) structures across multiple time series. This can be applied to drawing group-level brain connectivit
Externí odkaz:
http://arxiv.org/abs/2105.07196
Since the manual detection of electrographic seizures in continuous electroencephalogram (EEG) monitoring is very time-consuming and requires a trained expert, attempts to develop automatic seizure detection are diverse and ongoing. Machine learning
Externí odkaz:
http://arxiv.org/abs/1908.00492
Autor:
Kittipong Songsiri, Kreangsak Tamee
Publikováno v:
วารสารวิทยาการสารสนเทศและเทคโนโลยีประยุกต์, Vol 4, Iss 2, Pp 99-113 (2022)
Data warehouse technology is useful for managing large data. The purpose of them are analyzing organization’s datasets to formulate a strategy and direction of the organization. In this paper have present method of the development of data warehouse
Externí odkaz:
https://doaj.org/article/5199b305ac704edea37fb2a8bfdf1a08
Path analysis is a model class of structural equation modeling (SEM), which it describes causal relations among measured variables in the form of a multiple linear regression. This paper presents two estimation formulations, one each for confirmatory
Externí odkaz:
http://arxiv.org/abs/1809.06156
Autor:
Kantavat, Pittipol, Kijsirikul, Boonserm, Songsiri, Patoomsiri, Fukui, Ken-ichi, Numao, Masayuki
We propose new methods for Support Vector Machines (SVMs) using tree architecture for multi-class classi- fication. In each node of the tree, we select an appropriate binary classifier using entropy and generalization error estimation, then group the
Externí odkaz:
http://arxiv.org/abs/1708.08231
Autor:
van de Steen, Frederik, Faes, Luca, Karahan, Esin, Songsiri, Jitkomut, Sosa, Pedro Antonio Valdes, Marinazzo, Daniele
Many different analysis techniques have been developed and applied to EEG recordings that allow one to investigate how different brain areas interact. One particular class of methods, based on the linear parametric representation of multiple interact
Externí odkaz:
http://arxiv.org/abs/1607.03687
Autor:
Muhammad Riddha Abdul Rahman, Aini Ismafairus Abd Hamid, Nor Azila Noh, Hazim Omar, Wen Jia Chai, Zamzuri Idris, Asma Hayati Ahmad, Diana Noma Fitzrol, Ab. Rahman Izaini Ghani Ab. Ghani, Wan Nor Azlen Wan Mohamad, Mohamed Faiz Mohamed Mustafar, Muhammad Hafiz Hanafi, Mohamed Faruque Reza, Hafidah Umar, Mohd Faizal Mohd Zulkifly, Song Yee Ang, Zaitun Zakaria, Kamarul Imran Musa, Azizah Othman, Zunaina Embong, Nur Asma Sapiai, Regunath Kandasamy, Haidi Ibrahim, Mohd Zaid Abdullah, Kannapha Amaruchkul, Pedro Valdes-Sosa, Maria Luisa-Bringas, Bharat Biswal, Jitkomut Songsiri, Hamwira Sakti Yaacob, Putra Sumari, Paramjit Singh Jamir Singh, Azlinda Azman, Jafri Malin Abdullah
Publikováno v:
Frontiers in Neuroscience, Vol 16 (2022)
The debilitating effect of traumatic brain injury (TBI) extends years after the initial injury and hampers the recovery process and quality of life. In this study, we explore the functional reorganization of the default mode network (DMN) of those af
Externí odkaz:
https://doaj.org/article/0412bc0d195d402ca49d752409470607
Multi-class classification is mandatory for real world problems and one of promising techniques for multi-class classification is Error Correcting Output Code. We propose a method for constructing the Error Correcting Output Code to obtain the suitab
Externí odkaz:
http://arxiv.org/abs/1312.7179
Publikováno v:
Songklanakarin Journal of Science and Technology (SJST), Vol 41, Iss 5, Pp 1076-1083 (2019)
In this present work, organo-modified rice husk (SMRH) adsorbent was prepared by using cetyltrimethyl ammonium bromide (CTAB) for removing Congo red (CR), a model anionic dye, from aqueous solution. The FTIR analysis indicated that CTAB was adsorbe
Externí odkaz:
https://doaj.org/article/4942477ee1a44903989a89a7005e4cd6