Opportunistic Self Organizing Migrating Algorithm for Real-Time Dynamic Traveling Salesman Problem

Self Organizing Migrating Algorithm (SOMA) is a meta-heuristic algorithm based on the self-organizing behavior of individuals in a simulated social environment. SOMA performs iterative computations on a population of potential solutions in the given search space to obtain an optimal solution. In this paper, an Opportunistic Self Organizing Migrating Algorithm (OSOMA) has been proposed that introduces a novel strategy to generate perturbations effectively. This strategy allows the individual to span across more possible solutions and thus, is able to produce better solutions. A comprehensive analysis of OSOMA on multi-dimensional unconstrained benchmark test functions is performed. OSOMA is then applied to solve real-time Dynamic Traveling Salesman Problem (DTSP). The problem of real-time DTSP has been stipulated and simulated using real-time data from Google Maps with a varying cost-metric between any two cities. Although DTSP is a very common and intuitive model in the real world, its presence in literature is still very limited. OSOMA performs exceptionally well on the problems mentioned above. To substantiate this claim, the performance of OSOMA is compared with SOMA, Differential Evolution and Particle Swarm Optimization.Comment: 6 pages, published in CISS 201

Study the Effects of Nanohybrid Polymers / Polymer Nanocomposites on the Flow Behaviour of Indian Waxy Crude Oil

NO ABSTRAC

COMPARATIVE ANTIMICROBIAL SCREENING OF SATVA (SEDIMENTED STARCHY AQUEOUS EXTRACT) AND GHANA (SOLIDIFIED AQUEOUS EXTRACT) OF GUDUCHI (TINOSPORA CORDIFOLIA (WILLD.) MIERS)

Abstract: Guduchi (Tinospora cordifolia (Willd.) Miers) is incredibly versatile vine in ayurvedic system of medicine since ancient times and is indicated for potential use in wide range of diseases. Recent reports investigated and ascertained its role as a potent antimicrobial herb. Guduchi Satva and Ghana are popularly known formulations in ayurvedic fraternity for their huge therapeutic credentials. However, no published reports on comparative antimicrobial profile of Guduchi Satva and Ghana are available. Present study was therefore attempted to evaluate comparative antimicrobial efficacies of these two dosage forms of Guduchi: Satva and Ghana. Recommended microbial strain like; Salmonella typhi, Escherichia coli, P. aeruginosa and Staphylococcus aureus were used in this study for the same purpose. Both samples showed significant antibacterial activity and possess great potential against microorganisms. Phytochemical analysis for various functional groups revealed the presence of glycosides, alkaloids, tannins, phenols, starch and sterols in GG, while presence of only alkaloids and starch in GS., which suggests the alkaloidal contents  might be accountable for their antimicrobial potential. No microbial load was detected within both samples. The results also validate the traditional uses of Guduchi in various skin ailments and infectious disorders. Present study may prove a torch bearer for future studies to understand its biological activities.Keywords: Antimicrobial activity, Guduchi, Guduchi Ghana, Physicochemical, Tinospora cordifoli

India: digital divide and the promise of vaccination for all

CoWIN, an app and website to book appointments to be vaccinated, was introduced by the Government of India to vaccinate its population. However, a recent ruling by India’s apex court has drawn attention to the unfair and unequal nature of this policy towards its citizens in a country marred by illiteracy, bad internet connectivity, skewed digital infrastructure, and lack of a wider digital and public health infrastructure. Rohit Sharma analyses this recent verdict, and suggests possible ways to overcome the problems

Sentiment Analysis for Customer’s Reviews using Hybrid Approach

One of the greatest challenges to human-machine interaction is estimating the speaker’s emotion. The need is for clear, more accurate information about consumer preferences has led to increasing interest in high-level analysis of online media context. In this paper, I have proposed an approach for emotion recognition based on both speech and media content. Most of the existing approaches to sentiment analysis focus on audio and text sentiment. The novelty in this approach is the generation of text sentiments, audio sentiments and blend them to obtain better accuracy