Monitoring of forskolin production from roots and callus by HPTLC in Coleus forskohlii Briq.

High Performance Thin Layer Chromatography was a sensitive and accurate method for detection and estimation of forskolin in roots and by tissue culture of Coleus forskohlii. Maximum absorption was observed at 315 nm using fluorodensitometric analyis. Forskolin production was observed in callus cultures from leaf, stem and root origin as well as roots of in vitro grown plants. &nbsp

Automatic Leather Species Identification using Machine Learning Techniques

Content: Identification and classification of leather species becomes valuable and necessary due to concerns regarding consumer protection, product counterfeiting, and dispute settlement in the leather industry. Identification and classification of leather into species is carried out by histological examination or molecular analysis based on DNA. Manual method requires expertise, training and experience, and due to involvement of human judgment disputes are inevitable thus a need to automate the leather species identification. In the present investigation, an attempt has been made to automate leather species identification using machine learning techniques. A novel non-destructive leather species identification algorithm is proposed for the identification of cow, buffalo, goat and sheep leathers. Hair pore pattern was segmented efficiently using k-means clustering algorithm Significant features representing the unique characteristics of each species such as no.of hair pores, pore density, percent porosity, shape of the pores etc., were extracted. The generated features were used for training the Random forest classifier. Experimental results on the leather species image library database achieved an accuracy of 87 % using random forest as classifier, confirming the potentials of using the proposed system for automatic leather species classification. Take-Away: Novel technique to identify leather species Non destructive method Machine learning algorithms to automate leather species identificatio

Monitoring of forskolin production from roots and callus by HPTLC in Coleus forskohlii Briq.

High Performance Thin Layer Chromatography was a sensitive and accurate method for detection and estimation of forskolin in roots and by tissue culture of Coleus forskohlii. Maximum absorption was observed at 315 nm using fluorodensitometric analyis. Forskolin production was observed in callus cultures from leaf, stem and root origin as well as roots of in vitro grown plants. &nbsp

Efficient Storage and Processing Of High Volume Network Monitoring Data

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IoT-based Secure Data Transmission Prediction using Deep Learning Model in Cloud Computing

The security of Internet of Things (IoT) networks has become highly significant due to the growing number of IoT devices and the rise in data transfer across cloud networks. Here, we propose Generative Adversarial Networks (GANs) method for predicting secure data transmission in IoT-based systems using cloud computing. We evaluated our model’s attainment on the UNSW-NB15 dataset and contrasted it with other machine-learning (ML) methods, comprising decision trees (DT), random forests, and support vector machines (SVM). The outcomes demonstrate that our suggested GANs model performed better than expected in terms of precision, recall, F1 score, and area under the receiver operating characteristic curve (AUC-ROC). The GANs model generates a 98.07% accuracy rate for the testing dataset with a precision score of 98.45%, a recall score of 98.19%, an F1 score of 98.32%, and an AUC-ROC value of 0.998. These outcomes show how well our suggested GANs model predicts secure data transmission in cloud-based IoT-based systems, which is a crucial step in guaranteeing the confidentiality of IoT networks

Insights from within activity based learning (ABL) classrooms in Tamil Nadu, India: Teachers perspectives and practices

Quality has been an Education for All (EFA) goal since the 2000 Dakar framework positioned it ‘at the heart of education’ as a fundamental determinant of student enrolment, retention and achievement. Over the years, classroom pedagogy has been consistently regarded as ‘the crucial variable for improving learning outcomes’ (e.g., Hattie, 2009) and is thus seen as critical to reforms aimed at improving educational quality (UNESCO, 2005 p.152). The quality of teacher–pupil classroom interaction remains of central importance, rather research evidence (e.g., Borich, 1996) suggests that it is the single most important factor accounting for wide variation in the learning attainments of students who have used the same curriculum materials and purportedly experienced similar teaching methods. Other more recent studies (e.g., Aslam and Kingdon, 2011) have also reported that teacher ‘process’ variables have a more significant impact on student achievement than standard background characteristics. In the current era of the ‘global learning crisis’ (UNESCO, 2014) many developing economies have embarked on major pedagogical reforms. In India, the notion of energising schools and transforming classrooms has received unprecedented attention in the last 15 years. A number of programmes have been introduced in various states to provide meaningful access (Jandhyala and Ramachandran, 2007). The Activity Based Learning (ABL) Programme is one such effort to change the nature of teaching and learning in mainstream classrooms. In a national context, where there are innumerable on-going efforts aimed at pedagogical reform, ABL is hailed as a success story in terms of replication of a small model to a grand scale. From modest beginnings in 2003 in 13 Chennai (the capital city of Tamil Nadu) schools, ABL was rolled out in a phased manner across the entire state of Tamil Nadu for all children in classes 1–4, in all government and aided schools. The last few years have witnessed its adaptation under various guises in several other Indian states, such as Ekalavya in Madhya Pradesh, Digantar in Rajasthan and Nali Kali in Karnataka. Efforts to promote it internationally in other parts of the developing world, such as Ghana, Bangladesh, Ethiopia and Mozambique (Fennell and Shanmugam, 2016)have also been made. Though as Nudzor et al., 2015 note it has been met with mixed success in the case of Ghana. Nonetheless, ABL is an interesting programme to examine given its rapid growth and international outreach.The project was funded by Department for International Development (DFID, India)