Darknet Markets Analysis & Business Intelligence

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Description
In the era of big data, the impact of information technologies in improving organizational performance is growing as unstructured data is increasingly important to business intelligence. Daily data gives businesses opportunities to respond to changing markets. As a result, many…

In the era of big data, the impact of information technologies in improving organizational performance is growing as unstructured data is increasingly important to business intelligence. Daily data gives businesses opportunities to respond to changing markets. As a result, many companies invest lots of money in big data in order to obtain adverse outcomes. In particular, analysis of commercial websites may reveal relations of different parties in digital markets that pose great value to businesses. However, complex e­commercial sites present significant challenges for primary web analysts. While some resources and tutorials of web analysis are available for studying, some learners especially entry­level analysts still struggle with getting satisfying results. Thus, I am interested in developing a computer program in the Python programming language for investigating the relation between sellers’ listings and their seller levels in a darknet market. To investigate the relation, I couple web data retrieval techniques with doc2vec, a machine learning algorithm. This approach does not allow me to analyze the potential relation between sellers’ listings and reputations in the context of darknet markets, but assist other users of business intelligence with similar analysis of online markets. I present several conclusions found through the analysis. Key findings suggest that no relation exists between similarities of different sellers’ listings and their seller levels in rsClub Market. This study can become a great and unique example of web analysis and create potential values for modern enterprises.
Date Created
2018-05
Agent

Stable and Solubilized Active Au Atom Clusters for Selective Epoxidation of Cis-Cyclooctene With Molecular Oxygen

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Description

The ability of Au catalysts to effect the challenging task of utilizing molecular oxygen for the selective epoxidation of cyclooctene is fascinating. Although supported nanometre-size Au particles are poorly active, here we show that solubilized atomic Au clusters, present in…

The ability of Au catalysts to effect the challenging task of utilizing molecular oxygen for the selective epoxidation of cyclooctene is fascinating. Although supported nanometre-size Au particles are poorly active, here we show that solubilized atomic Au clusters, present in ng ml-1 concentrations and stabilized by ligands derived from the oxidized hydrocarbon products, are active. They can be formed from various Au sources. They generate initiators and propagators to trigger the onset of the auto-oxidation reaction with an apparent turnover frequency of 440 s-1, and continue to generate additional initiators throughout the auto-oxidation cycle without direct participation in the cycle. Spectroscopic characterization suggests that 7–8 atom clusters are effective catalytically. Extension of work based on these understandings leads to the demonstration that these Au clusters are also effective in selective oxidation of cyclohexene, and that solubilized Pt clusters are also capable of generating initiators for cyclooctene epoxidation.

Date Created
2017-03-28
Agent
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