Supervised discriminant analysis for droplet micro-magnetofluidics
نویسندگان
چکیده
منابع مشابه
Supervised discriminant analysis for droplet micro-magnetofluidics
We apply the technique of supervised discriminant analysis (SDA) for in-flow detection in droplet-based magnetofluidics. Based on the SDA, we successfully discriminate bivariant droplets of different volumes containing different encapsulated magnetic content produced by a GMR-based lab-on-chip platform. We demonstrate that the accuracy of discrimination is superior when the correlation of varia...
متن کاملStrong Ferromagnetically-Coupled Spin Valve Sensor Devices for Droplet Magnetofluidics
We report a magnetofluidic device with integrated strong ferromagnetically-coupled and hysteresis-free spin valve sensors for dynamic monitoring of ferrofluid droplets in microfluidics. The strong ferromagnetic coupling between the free layer and the pinned layer of spin valve sensors is achieved by reducing the spacer thickness, while the hysteresis of the free layer is eliminated by the inter...
متن کاملSemi-supervised sub-manifold discriminant analysis
In this paper we present a semi-supervised sub-manifold discriminant analysis algorithm. To separate each sub-manifold constructed by each class, we define the within-manifold scatter, between-manifold scatter and total-manifold scatter matrices. The scatter matrices are robust to outlier and diverse-density clusters. Kernelization and direct non-linear embedding are also developed. Experimenta...
متن کاملSemi-supervised Discriminant Analysis Via CCCP
Linear discriminant analysis (LDA) is commonly used for dimensionality reduction. In real-world applications where labeled data are scarce, LDA does not work very well. However, unlabeled data are often available in large quantities. We propose a novel semi-supervised discriminant analysis algorithm called SSDACCCP . We utilize unlabeled data to maximize an optimality criterion of LDA and use t...
متن کاملSemi-Supervised Discriminant Analysis via Spectral Transduction
Deming Zhai1 [email protected] Hong Chang2 [email protected] Bo Li1 [email protected] Shiguang Shan2 [email protected] Xilin Chen2 [email protected] Wen Gao13 [email protected] 1 School of Computer Science and Technology, Harbin Institute of Technology, Harbin, China 2 Key Laboratory of Intelligent Information Processing, Chinese Academy of Sciences, Beijing,China 3 Institute of Digital Media, Peking Univ...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Microfluidics and Nanofluidics
سال: 2015
ISSN: 1613-4982,1613-4990
DOI: 10.1007/s10404-015-1579-z