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Information Technology (IT) governance is a combination of processes and controls to increase the success rate of projects, programs, and portfolios. We have several research articles evidencing the stability of classification techniques into medical, security, sports, artificial intelligence, software project management, etc. The utilization of classification techniques such as Naïve Bayes algorithm in software governance has unique advantages in terms of accuracy. The approach in this article would help to provide key management insights to make precise decisions and improve the overall success rate of the software projects, programs and portfolios. Naïve Bayes algorithm is used to logically validate the alignment of governance policies and project details through Weka (Waikato Environment of Knowledge Analysis). Weka is a collection of machine learning algorithms for data mining tasks. IT governance policies are used as a benchmark for validation and processed with Naïve Bayes algorithm in Weka Governance team members would be an interface to communicate and set expectations with the project manager. Basic governance standards across Software Development Lifecycle (SDLC) are defined and used as a bench mark in the governance assessment form. These predefined governance assessment forms and project details are validated through Naïve Bayes algorithm. This proactive model and adherence to the governance standards would help to increase the success rate of IT projects. [ABSTRACT FROM AUTHOR]

Laccase is belonging to the oxidases of blue multi-copper and will be participating in polymer degradation, monomer cross-linking and aromatic compounds' ring cleavage. This is distributed widely in fungi and higher plants. This is also present in Deuteromycetes, Basidiomycetes and Ascomycetes and also much abundant in white-rot fungi which are lignin-degrading. Also it is used in synthesizing organic substances, having phenols and amines as typical substrates with reaction products as oligomers and dimers which are derived out of coupling from radical reactive intermediates. In recent time, these enzymes are gaining application in fields like paper and pulp, food and textile industry. Also of late it is used in biofuel cells, biosensors design, and also a tool for medical diagnostics and an agent for bioremediation in cleaning up certain explosives and pesticides in soil as well as herbicides. This present work is focusing on screening, the process optimization in achieving maximum production with partial purification in extracellular laccases by Pseudomonas aeruginosa. Purification of laccase through filtrate of bacterium culture is achieved as a greatest action after the utilization of DEAE-Sephadex Affinity chromatography, chromatography (Sephadex) of Gel filtration and precipitation of ammonium sulphate. The experimental results are showing better performance in purification and production of laccase through Pseudomonas Aeruginosa. [ABSTRACT FROM AUTHOR]

Social networks are becoming more popular platforms for communication, interaction and collaboration among relatives & friends. Researchers have recently come out with an emerging class of technology that leverage relationships from social networks to improve security in applications such as electronic mail, overlay routing and web browsing. Peer-to-peer systems are mostly vulnerable to Sybil attacks. The Sybil attack is an attack where an adversary creates multiple Duplicate or False identities to compromise the running of the system. By including false information by the Duplicated entities, an adversary can mislead a system into making decisions benefiting. Defending against Sybil attacks is quite challenging. Over the last few years, there are so many approaches suggested to overcome such issues of fake user behavior but there remain some issues unaddressed. This work gives a novel Sybil attack detection and removal mechanism based on behavioral analysis and neighbor similarity calculation named Enhanced Similarity based Sybil Detection Mechanism (ESSDM). In this approach, neighbor nodes acquainting with more familiarity are identified as the duplicated Sybil nodes. By applying our enhanced similarity based Sybil detection mechanism, the results show that the Sybil attack is considerably minimized, thereby improving security and its performance level. [ABSTRACT FROM AUTHOR]

Flower development at the shoot apex is initiated in response to environmental cues. Day length is one of the most important of these and is perceived in the leaves. A systemic signal, called the floral stimulus or florigen, is then transmitted from the leaves through the phloem and induces floral development at the shoot apex. Genetic analysis in Arabidopsis identified a pathway of genes required for the initiation of flowering in response to day length. The nuclear zinc-finger protein CONSTANS (CO) plays a central role in this pathway, and in response to long days activates the transcription of FT, which encodes a RAF-kinase-inhibitor-like protein. We show using grafting approaches that CO acts non-cell autonomously to trigger flowering. Although CO is expressed widely, its misexpression from phloem-specific promoters, but not from meristem-specific promoters, is sufficient to induce early flowering and complement the co mutation. The mechanism by which CO triggers flowering from the phloem involves the cell-autonomous activation of FT expression. Genetic approaches indicate that CO activates flowering through both FT-dependent and FT-independent processes, whereas FT acts both in the phloem and the meristem to trigger flowering. We propose that, partly through the activation of FT, CO regulates the synthesis or transport of a systemic flowering signal, thereby positioning this signal within the established hierarchy of regulatory proteins that controls flowering.