A number of pharmaceutical steroid synthons are currently produced through the microbial side-chain cleavage of natural sterols as an alternative to multi-step chemical synthesis. Industrially, these synthons have been usually produced through fermentative processes using environmental isolated microorganisms or their conventional mutants. Mycobacterium smegmatis mc2 155 is a model organism for...

Dyna planning is an efficient way of learning from real and imaginary experience. Existing tabular and linear Dyna algorithms are single-step, because an “imaginary” feature is predicted only one step into the future. In this paper, we introduce a multi-step Dyna planning that predicts more steps into the future. Multi-step Dyna is able to figure out a sequence of multi-step results when a real...

Abstract Layer actions response time is a critical indicator of cloud geographical information services (cloud GIS Services), which great significance to resource allocation and schedule optimization. However, since are highly dynamic, uncertain, uncontrollable, the layer influenced by spatiotemporal intensity concurrent access intensity, posing significant challenges in predicting action time....

The Supply Chain is considered a necessity for the success of organizations seeking the most economic, environmental and social impacts. In addition, the implementation and suitable execution of this supply chain seems to be necessary. Considering the importance of the social impacts of this supply chain, a fuzzy multi-objective mathematical model is provided such that, in addition to consideri...

This paper proposes a method to neutralize the pose of facial databases. Efficient use of the feature extractors and its properties leads to the pose neutralization. Feature extractors discussed here are few transforms like Discrete Cosine Transform (DCT) and Discrete Fourier Transform (DFT). Symmetric behavior of transforms is the basis of the proposed method. Modulo based approach in extracti...

We present a method for learning discriminative feature transforms using as criterion the mutual information between class labels and transformed features. Instead of a commonly used mutual information measure based on Kullback-Leibler divergence, we use a quadratic divergence measure, which allows us to make an efficient non-parametric implementation and requires no prior assumptions about cla...

Dense feature extraction is becoming increasingly popular in face recognition. Face recognition is a vital component for authorization and security. In earlier days, CCA (Canonical Correlation Analysis) and SIFT (Scale Invariant Feature Transforms) was used for face recognition. Since multi scale extraction is not possible with these existing methods, a new approach to dense feature extraction ...