A novel two-core optical fiber probe is proposed and fabricated by grinding method. The distribution of the optical field
emerging from the probe was simulated using BPM method. With the probe, a single fiber optic tweezers system was
constructed and successfully used to trap and rotate microscopic particles. The structure of this system is simple and
compact. With the merit of easily controlling and adjusting, this novel system can adapt to the optical micromanipulation
need of more biological cells and molecular.
A novel in-fiber optical switch based on two-core optical fiber is demonstrated. A Mach-Zehnder intereferometer was integrated into a single optical fiber of 125 μm diameter using a novel coupling connection technology. Then embedding the single optical fiber into a universal optical fiber transmission line, the novel in-fiber optical switch is formed. It can make microscale and integrated optical fiber elements into a complex function system, which greatly improve the performance of in-fiber elements and can develop and manufacture fiber optical sensors acceptable for various special situation. The reference and sensing arms of the intereferometer of the perfect in-fiber optical switch based on two-core optical fiber is integrated into a single fiber, which makes the structure more simple and the optical paths relatively stable, so it can effectively avoid the influence of enviroment factors such as vibration, temperature and greatly improve the performance of in-fiber optical swiches.
A novel flat-faced thin fiber optic tweezers is proposed. It was fabricated by heating and drawing method under the
condition of laying aside the conventional focusing method. With this fiber optic probe, the single fiber optic tweezers
realized trapping a yeast cell in water. The experiment results were in good agreement with the simulated results which
were carried out using FDTD method.
Rough Set is a valid mathematical theory developed in recent years, which has the ability to deal with imprecise, uncertain, and vague information. It has been applied in such fields as machine learning, data mining, intelligent data analyzing and control algorithm acquiring successfully. Many researchers have studied rough sets in different view. In this paper, the authors discuss the reduction of knowledge using information entropy in rough set theory. First, the changing tendency of the conditional entropy of decision attributes given condition attributes is studied from the viewpoint of information. Then, two new algorithms based on conditional entropy are developed. These two algorithms are analyzed and compared with MIBARK algorithm. Furthermore, our simulation results show that the algorithms can find the minimal reduction in most cases.
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