Deep Convolutional Neural Network (Falcon) and transfer learning‐based approach to detect malarial parasite

Deep learning models have already benchmarked its demonstration in the applications of Medical Sciences. Present day medical industries suffer due to deadly disease such as malaria etc. As per the report from World Health Organization (WHO), it is noted that the amount of caution and care taken per patient by a human doctor to cure malaria is decreasing. To address this issue, this paper proposes an automated solution for the detection of malaria from the real-time image. The key idea of the proposed solution is to use a Deep Convolutional Neural Network (DCNN) called “Falcon” to detect the parasitic cells from blood smeared slide images of Malaria Screener. Furthermore, the class accuracy of the given dataset samples is maintained in order to model not only the normal case but to accurately predict the presence of malaria as well. Experimental results confirms that the model does not possess overfitting, class imbalance, and provides a reasonable classification report and trustworthy accuracy with 95.2?% when compared to the state-of-the-art Convolutional Neural Network (CNN) models.

     

如何穿越团队协作的五重障碍

信任缺失、惧怕冲突、承诺不足、逃避担责、漠视结果,这是团队协作的五重障碍,一环扣一环;而敏捷实践有助于团队穿越这五重障碍,迈向成功。自古以来,那些地位尊崇的理念、宗旨和经验,和长盛不衰的经济、社会和情感的价     

Nanopatterned cadmium selenide Langmuir-Blodgett platform for leukemia detection

We present results of the studies relating to preparation of Langmuir-Blodgett (LB) monolayers of tri-n-octylphosphine oxide-capped cadmium selenide quantum dots (QCdSe) onto indium-tin oxide (ITO) coated glass substrate. The monolayer behavior has been studied at the air-water interface under various subphase conditions. This nanopatterned platform has been explored to fabricate an electrochemical DNA biosensor for detection of chronic myelogenous leukemia (CML) by covalently immobilizing the thiol-terminated oligonucleotide probe sequence via a displacement reaction. The results of electrochemical response studies reveal that this biosensor can detect target DNA in the range of 10(-6) to 10(-14) M within 120 s, has a shelf life of 2 months, and can be used about 8 times. Further, this nucleic acid sensor has been found to distinguish the CML-positive and the control negative clinical patient samples.     

Optimal Route Network Design for Transit Systems Using Genetic Algorithms

The paper proposes a technique for the development of "optimal" transit route networks (for example, a bus route network) given the information on link travel times and transit demand. The proposed method, unlike previous techniques, primarily uses optimization tools for the development of the transit route network--the reliance on heuristics is minimal. In the proposed method, genetic algorithms, an evolutionary optimization technique, is used to develop the "optimal" set of routes. Results show that the proposed procedure performs better than the existing techniques.