Assessment of glaucoma using extreme learning machine and fractal feature analysis

Dear Sir,Iam Dr.Kavitha S,from the Department of Electronics and Communication Engineering,Nandha Engineering College,Erode,Tamil Nadu,India.I write to present the detection of glaucoma using extreme learning machine(ELM)and fractal feature analysis.Glaucoma is the second most frequent cause of permanent blindness in industrial

A review of the techniques for the mold manufacturing of micro/nanostructures for precision glass molding

Micro/nanostructured components play an important role in micro-optics and optical engineering,tribology and surface engineering,and biological and biomedical engineering,among other fields.Precision glass molding technology is the most efficient method of manufacturing micro/nanostructured glass components,the premise of which is meld manufacturing with complementary micro/nanostructures.Numerous mold manufacturing methods have been developed to fabricate extremely small and high-quality micro/nanostructures to satisfy the demands of functional micro/nanostructured glass components for various applications.Moreover,the service performance of the mold should also be carefully considered.This paper reviews a variety of technologies for manufacturing micro/nanostructured molds.The authors begin with an introduction of the extreme requirements of mold materials.The following section provides a detailed survey of the existing micro/nanostructured mold manufacturing techniques and their corresponding mold materials,including nonmechanical and mechanical methods.This paper concludes with a detailed discussion of the authors recent research on nickel-phosphorus(Ni-P)mold manufacturing and its service performance.

Fatigue driving detection based on Haar feature and extreme learning machine

As the significant branch of intelligent vehicle networking technology, the intelligent fatigue driving detection technology has been introduced into the paper in order to recognize the fatigue state of the vehicle driver and avoid the traffic accident. The disadvantages of the traditional fatigue driving detection method have been pointed out when we study on the traditional eye tracking technology and traditional artificial neural networks. On the basis of the image topological analysis technology, Haar like features and extreme learning machine algorithm, a new detection method of the intelligent fatigue driving has been proposed in the paper. Besides, the detailed algorithm and realization scheme of the intelligent fatigue driving detection have been put forward as well. Finally, by comparing the results of the simulation experiments, the new method has been verified to have a better robustness, efficiency and accuracy in monitoring and tracking the drivers＇ fatigue driving by using the human eye tracking technology.