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Статті в журналах з теми "Bionsensor"
Benitez, L., A. Martin-Gonzalez, P. Gilardi, T. Soto, J. Rodriguez Lecea, and J. C. Gutiérrez. "The ciliated protozoa Tetrahymena thermophila as a bionsensor to detect mycotoxins." Letters in Applied Microbiology 19, no. 6 (December 1994): 489–91. http://dx.doi.org/10.1111/j.1472-765x.1994.tb00989.x.
Повний текст джерелаHiggins, I. J. "Molecular electronics: bionsensors and biocomputers." Biosensors and Bioelectronics 6, no. 1 (January 1991): 74–75. http://dx.doi.org/10.1016/0956-5663(91)85011-k.
Повний текст джерелаLoibner, A. P., O. Doblhoff-Dier, N. Zach, K. Bayer, H. Katinger, Ch Lobmaier, Th Schalkhammer, and F. Pittner. "Automated glucose measurement with microstructured thin-layer bionsensors for the control of fermentation processes." Sensors and Actuators B: Chemical 19, no. 1-3 (April 1994): 603–6. http://dx.doi.org/10.1016/0925-4005(93)01099-p.
Повний текст джерелаGooding, J. J. "Optical Bionsensors: Present and Future(Eds Frances S. Ligler and Chris A. Rowe Taitt)." Australian Journal of Chemistry 55, no. 9 (2002): 617. http://dx.doi.org/10.1071/ch02008_br.
Повний текст джерелаShao, Bin, Hongshuo Chen, Chuanjin Cui, Jing Li, and Ruikun Gonge. "Research Progress on Improvement of Conductivity of MOFs and Their Application in Bionsensors: A Review." Chemistry Letters 50, no. 4 (April 5, 2021): 714–23. http://dx.doi.org/10.1246/cl.200808.
Повний текст джерелаZhang, Huayue, Lu Yang, Xiaqing Zhu, Yanyan Wang, Haitao Yang, and Zefang Wang. "Thrombin Bionsensors: A Rapid and Ultrasensitive Thrombin Biosensor Based on a Rationally Designed Trifunctional Protein (Adv. Healthcare Mater. 12/2020)." Advanced Healthcare Materials 9, no. 12 (June 2020): 2070038. http://dx.doi.org/10.1002/adhm.202070038.
Повний текст джерелаTravas-sejdic, Jadranka. "Novel materials promise faster and simpler bionsensors for gene detection." SPIE Newsroom, 2006. http://dx.doi.org/10.1117/2.1200603.0106.
Повний текст джерелаДисертації з теми "Bionsensor"
Isabel, Alejandra. "Bacteriophage 186 - Investigating the role of transcriptional regulators CI, Apl, CII and Tum at the lytic/lysogenic switch during 186 prophage induction." Thesis, 2020. http://hdl.handle.net/2440/128817.
Повний текст джерелаThesis (Ph.D.) -- University of Adelaide, School of Biological Sciences, 2020
Muhammad, Atif. "A computationally efficient framework for large-scale distributed fingerprint matching." Thesis, 2017. https://hdl.handle.net/10539/23747.
Повний текст джерелаBiometric features have been widely implemented to be utilized for forensic and civil applications. Amongst many different kinds of biometric characteristics, the fingerprint is globally accepted and remains the mostly used biometric characteristic by commercial and industrial societies due to its easy acquisition, uniqueness, stability and reliability. There are currently various effective solutions available, however the fingerprint identification is still not considered a fully solved problem mainly due to accuracy and computational time requirements. Although many of the fingerprint recognition systems based on minutiae provide good accuracy, the systems with very large databases require fast and real time comparison of fingerprints, they often either fail to meet the high performance speed requirements or compromise the accuracy. For fingerprint matching that involves databases containing millions of fingerprints, real time identification can only be obtained through the implementation of optimal algorithms that may utilize the given hardware as robustly and efficiently as possible. There are currently no known distributed database and computing framework available that deal with real time solution for fingerprint recognition problem involving databases containing as many as sixty million fingerprints, the size which is close to the size of the South African population. This research proposal intends to serve two main purposes: 1) exploit and scale the best known minutiae matching algorithm for a minimum of sixty million fingerprints; and 2) design a framework for distributed database to deal with large fingerprint databases based on the results obtained in the former item.
GR2018